I started this website in 2011, and I cannot remember a more unstable time to be a marketer or run an online business. Consider the following…

1. Platform Instability.

We haven’t seen anything like what we’re seeing right now. Simply consider everything that has happened during the past couple of years, with most of it happening right now:

• Elon Musk dares users and advertisers to leave Twitter/X
• Meta launches Threads
• Mark Zuckerberg does his best Musk impersonation with Meta
• TikTok on the verge of an actual ban in the US

This is crazy. Just during the past year alone, consider all of the migration that has happened and will happen. Users left Twitter/X for Threads and BlueSky. Users are leaving Meta for [?]. Users migrating from TikTok to [?].

Speaking for myself, it wasn’t difficult to leave Twitter. But now we’re in a place where there are few good alternatives. Everything either feels corrupted, potentially corrupted, or in the early stages before that corruption happens.

There is going to be a lot of jumping around during the next few months, and it will be interesting to see where people fall and whether any new mainstream (and safe) solutions arise.

2. Distribution Instability.

This started a decade ago with Facebook’s news feed algorithm impacting outgoing traffic. Facebook was once a goldmine for organic traffic, but now it drives a fraction of what it once did.

Long-form self-hosted blogs gave way to short-form social media text posts. Facebook preferred links until it didn’t. Long-form video was king on YouTube before TikTok and Shorts arrived. Then Meta copied TikTok and featured Reels everywhere.

Distribution of content has been a pain point on every platform. Algorithms change. Creators are unable to reach their followers — or they’re unable to reach a new audience. The ebbs and flows and migrations of each platform drive uncertainty.

3. AI-Related Instability.

This, on top of everything else, is too much. Now human creators are competing with AI creators. Or they’re battling AI-generated comment spam. Google and other search engines are becoming AI answer engines, which impacts organic search referrals. Websites are published overnight with entirely AI-generated content.

It’s chaos. I’ve certainly been in the middle of it. While I wouldn’t claim to have the clear, definitive solution, I can share how I’m addressing it.

Here’s what I’m doing…

Platform Diversity

For years, we’ve heard that “You can’t be everywhere.” While true — and I echoed this advice — focusing on one or two platforms was pretty clearly a dangerous game.

As mentioned, I played this dangerous game myself. When it came to establishing a social media home base, I spent most of my time on Facebook. I mostly ignored every other platform. It wasn’t until 2022, when I started to pay for this decision, that I shifted that approach.

The suggestion that “you can’t be everywhere” is partly true and means well. Not every business has the resources to commit the time to establish an optimal presence on every platform — or most of the important ones.

But that kind of misses the point. You can still “be everywhere” while focusing on one or two.

Now that nearly every platform supports short-form video, it made for an easy distribution strategy. Every video I create goes to the following platforms:

• Facebook
• Instagram
• TikTok (for now)
• YouTube
• LinkedIn

I approach the LinkedIn videos somewhat differently, since I’ll add more written commentary. But otherwise, I’m repurposing the same video everywhere.

Is that ideal? No. The ideal scenario would be to have the dedicated resources to create unique content and spend the time to build a presence on each platform.

But I can’t do that. I won’t do that. And sharing the same content everywhere is better than the alternative of focusing entirely on one and putting all of my risk in that platform.

I built my TikTok presence from nothing to 35,000 followers in about two years. But I’m not at all concerned about losing that. If TikTok is banned, those people will have to go somewhere. My most loyal followers will find me elsewhere.

If you can create unique content on several platforms, great. But the bottom line is that platform diversity protects you in times of instability (like today).

Find the platform or two where you want to dedicate the most time connecting and building relationships. Otherwise, do what you can, but create a presence in as many places as you can. Find a way to do it as efficiently and effectively as possible.

Media and Content Diversity

My business was birthed by my blog. I wrote content, which attracted readers and subscribers. It created an opportunity to sell my own products.

I would experiment with a podcast and long-form video, but it was crystal clear that my business was blog-first during the first 10 years. The truth is I leaned too heavily into one form of content, which was a bad risk.

That became impossible to ignore when my business was spiraling in 2022. Facebook was no longer generating the organic clicks that it once did. Organic search referrals from Google slowly dropped from as much as 10,000 per day to under 1,000.

It was a painful lesson, but I committed myself to short-form video in late 2022. After publishing at least one video every day of 2023 and most of 2024, I’m focused on three per week in 2025.

I’ve established myself with short-form video now, so that allows me to better diversify the types of content I create. I continue to write a blog post every week, in addition to three short posts that feature my videos. And now I’m bringing back my podcast, but at a commitment level that is realistic.

Not everyone reads blogs. Not everyone consumes short-form video. Not everyone listens to podcasts. But if I create a little of all three, I have a better chance of reaching a more diverse audience.

Distribution Control

Another popular piece of advice is “Don’t build your house on rented land.” While I do believe that this advice is overly simplistic (and we rent a lot of the stuff our house is built on), the underlying point of ownership is valid.

A primary — if not the only — reason I still have a business is because of what I own or mostly own. This website and my email list have always been the engine that drive my business. It now gets more help than it once did from other distribution channels.

While my email list has always played a key part, I’m far more intentional and strategic now in 2025. I sent more traffic to my website from email in 2024 than I had in any year since 2017. That was done while sending far fewer emails in total volume — but more to those who were most engaged.

I’m tweaking that approach in 2025 to give my subscribers more control of email frequency while creating more opportunities to leverage email for cross promotions.

Following are the primary ways that you can subscribe to my content:

• Blog Alerts (1 per week)
• Video Alerts (3 per week)
• Podcast Alerts (1 per week)
• Weekly Recaps (1 per week)
• Cornerstone Advertising Tips (1 per week)
• The Full Funnel (every alert)

With this approach, you will get exactly what you subscribe to and very little else. The second half of emails will sometimes be dedicated to cross-promotion of subscriptions and paid products like my private membership and one-on-ones.

While this may at least temporarily hurt email-driven traffic to my website, I’m confident that it will result in a more engaged email list with less churn.

AI-Aware and Curious

We’re in a weird place with AI. It’s very easy to be overwhelmed by the velocity of change.

You can also get lost in trying to stay on top of it all — or aiming to use AI for everything. While AI can replace humans for repetitive tasks and be a good complementary tool, you can take it too far.

This might partly be my own creative resistance to AI content, but I believe that there will be an adjustment. AI-generated images, video, and even written content is novel now. There are cases when it can have value. There are others when it’s a huge annoyance, if not problematic or illegal (via theft).

I enjoy creating content, and I don’t want AI to replace that task for my own process. But I do use it for brainstorming and some editing tasks. I just wouldn’t consider myself AI-first in any way.

My favorite use of AI right now is my chatbot that is powered by more than 600 pages of my content. It became so good and popular that I finally had to move it from free to a members-only benefit. Some expressed their displeasure with this decision, but it was simply becoming too expensive. And people were using it in ways I never would have imagined.

We can’t stick our heads in the sand and hope that AI will go away. It won’t. We also don’t all need to be AI experts. Be aware and curious.

How is this relevant to the current discussion? AI may be able to help us with creation and distribution. We just need to balance the value of human vs. AI-generated content.

Paid Efforts

I hope you didn’t forget this one. It doesn’t matter how good your organic efforts, you should have some sort of paid strategy.

For me, that focus has always been with Meta advertising (obviously). Not much has changed here, though I’m certainly uneasy about Meta’s most recent decisions.

I’d like to tell you that my current focus on using ads for list building is somehow new, but it’s not. While I’ve also used ads for sales, quality traffic, and video engagement, list building has always been my best long-term investment.

Whether it’s Meta, Google, podcast ads, or something else, find a paid distribution channel to accelerate your efforts.

Your Turn

How has your approach changed to address these uncertain times?

Let me know in the comments below!

The post A Stable Marketing Strategy for Unstable Times appeared first on Jon Loomer Digital.

Meta ads conversion results are central to the job of an advertiser. They are our guiding light for helping us understand whether something is or isn’t working.

But conversion results can be misleading, if not outright lie. That could be because an advertiser is knowingly manipulating the data. It could also be that they aren’t knowledgable enough to understand the nuances.

The purpose of this guide is to help you master those important nuances so that you can evaluate your results accurately.

Let’s get to it…

Conversion Events

Conversion data is pointless if you don’t have the infrastructure in place that allows Meta to attribute conversions. This starts with defining conversion events.

When someone completes a purchase, you need to notify Meta that it happened. This can be done using the website pixel or conversions API (or both). Regardless, it’s up to you to define these actions and make sure that they are sent to Meta.

There are two primary ways that you can define conversion events.

1. Standard Events: Conversions that Meta will recognize (Purchase, Lead, Contact, etc.)
2. Custom Events: Conversions that fall outside of the definition of Standard Events

You can use standard events, custom events, and custom conversions for both optimization and reporting in Ads Manager. These need to be set up properly to get accurate results.

Defining Attribution

Attribution is how Meta gives credit to an ad for a reported conversion. In order to report a conversion, it must happen within the defined attribution windows after a paid impression.

Two ads cannot get credit for the same conversion. If a user was served different ads within the defined attribution window, credit goes to the ad that received the most recent click.

Click Attribution

Click attribution gives credit for a conversion if it happens within the defined attribution window following a click on your ad. For example:

1. January 1 (2pm): User clicks on Ad A
2. January 1 (4pm): User completes a purchase

In this example, Ad A is given credit for a conversion because it happened within a day of clicking on it. The attribution window is 7 days by default, but you might also see 1 day or 28 days (for reporting only).

The conversion does not need to happen immediately, as long as it happens within the attribution window. It could happen like this (assuming a 7-day click attribution setting):

1. January 1: User clicks your ad
2. January 5: User returns to your website and completes a purchase

It does not need to be the same link that they clicked on your original ad. All that matters is that they initially clicked and converted within the attribution window.

Note that the “click” on your ad can be any click. It does not need to be a click on an external link to your website. It could be a click on media, reactions, or something else. (SIDE NOTE: I’m not a fan of Meta defining it this way.)

Also, the reported conversion does not need to be for the item that you were promoting. Consider the following scenario:

1. User clicks ad that promotes Product A
2. User redirected to Product A landing page
3. User navigates to Product B landing page and completes a purchase
4. Purchase is reported

If the Results column reflects Purchases, it will include all attributed purchase events — which could be for multiple products, regardless of what was promoted.

View Attribution

View attribution gives credit for a conversion if it happens within the defined attribution window following a view of your ad (but no click). For example:

1. January 1 (2pm): User is shown Ad A, but does not click it
2. January 1 (4pm): User completes a purchase

In this case, a conversion is reported even though an ad was not clicked. Here is a common scenario for how a view-through conversion happens:

1. January 1 (2pm): User shown your ad
2. January 1 (4pm): User remembers the ad, Googles your product, and completes a purchase

While no click was made, it is assumed that the ad contributed to that purchasing decision.

Another common scenario can lead to inflated results:

1. January 1 (2pm): User is shown Ad A from Company A, but does not click it
2. January 1 (4pm): User receives an email from Company A and completes a purchase

While it’s possible that the user saw the ad and it contributed to the decision to make the purchase, it’s also possible that the impression made no impact on them at all. It’s impossible to know for sure.

View-through conversions have less value overall because no click was made to indicate that the ad itself inspired an action. But that doesn’t make them worthless.

Where view-through becomes especially problematic is when advertisers use remarketing strategies and highlight their elevated ROAS and inflated conversion results as evidence of their success. This can be misleading if it’s not made clear that the results came from remarketing.

Attribution Setting

The attribution setting is defined within the ad set when utilizing a Website conversion location and maximizing the number or value of conversions.

The default attribution setting is 7-day click, 1-day view, and 1-day engaged-view.

Engaged-view merely means that, when using video in your ads, Meta will focus on people who watch at least 10 seconds of it before converting — regardless of whether the conversion is attributed from a click or view.

You can change any of these settings…

Here are your options:

• Click Attribution: 7-day or 1-day
• Engaged-View: 1-day or None
• View-Through: 1-day or None

This setting will control two things:

1. How conversions are reported. Conversions will only be reported by default that qualify under your attribution setting. If you define the attribution setting as 1-day click, Meta will not report on conversions that happen beyond one day or via view-through (these other conversions can still be uncovered using the Compare Attribution Settings feature).

2. How ad delivery is optimized. Since Meta prioritizes getting you the results that you want, the attribution setting can impact how your ads are delivered. If you define the attribution setting as 1-day click only, your ads will be shown to people most likely to convert within that window.

Conversion Reporting

When maximizing the number or value of conversions, you will need to select a conversion event.

This event will be what fills the Results column in Ads Manager.

But you can add columns for other conversion events as well. Click to customize columns…

Then add columns for standard events, custom events (if they’ve been used in ads before), or custom conversions.

Even if your conversion event is a Purchase, you can view how many other conversions resulted from your ads.

Note that one person can perform multiple conversions.

Compare Attribution Settings

Conversion results require important context to make sense of them. Otherwise, results can be misleading or cover an important part of the story. This context is found by using the Compare Attribution Settings feature.

This feature is found when clicking the Columns dropdown menu (Compare Attribution Settings is right above Customize Columns).

By default, your conversion results will be based on the attribution setting defined within the ad set. But you can use this feature to see how those results break down — or even uncover conversions that happened beyond your attribution setting.

Select all of the attribution settings that you want. We’ll select them all for the fun of it…

Note that there’s an option for 28-day click, even though that option was phased out from attribution settings after iOS 14+ changes. While your default reporting will never exceed 7-day click now, you can still view conversions that occurred within 28 days of clicking.

Once selected, Meta will create a column for each attribution setting when viewing a type of conversion.

1. Purchases (36): There are 36 total purchases reported based on the attribution setting.

2. 1-Day View (12): 12 conversions happened within a day of viewing your ad (and not clicking).

3. 1-Day Engaged-View (0): A video was not used in the ad, so no engaged-view conversions are reported.

4. 1-Day Click (13): 13 conversions happened within a day of clicking on your ad.

5. 7-day Click (24): 24 conversions happened within 7 days of clicking on your ad.

6. 28-day Click (32): 32 conversions happened within 28 days of clicking on your ad.

Now we need to do a little math to decipher what this means…

1. 36 conversions happened within 7 days of clicking or 1 day of viewing the ad.

2. 11 conversions happened beyond 1 day but within 7 days of clicking the ad (24 minus 13).

3. 8 conversions happened beyond 7 days but within 28 days of clicking the ad (32 minus 24).

4. A total of 44 total conversions can be attributed to your ad (Total Purchases + those that happened beyond 7-day click).

The Compare Attribution Settings feature is a great tool for helping us understand how our results break down to get a better sense of the overall confidence we may have in them. Consider these scenarios:

1. 70% of conversions are 1-day view. With such results, I’d have less confidence that my ads truly contributed to all of these conversions.

2. 20% additional conversions happened beyond 7-day click. These are results that are not reported by default, but indicate that our ads made a greater impact than expected. This could be due to an email sequence post-conversion or a longer buying cycle for a high-priced product.

First Conversion Reporting

There’s another way to add important context to your results using Compare Attribution Settings, and it’s with First Conversion reporting.

When you select attribution settings, you’ll have the following three options…

By default, Meta reports all conversions that happen within the attribution window. For example, someone could make two separate purchases during a seven-day period. If that happens, you could have two attributed purchases within a 7-day click attribution window.

But First Conversion would only count the first attributed conversion of that type. You could have multiple purchases, registrations, and add-to-cart events that fall within the attribution window. When selecting First Conversion, only the first of each would be counted.

Allow me to share an example of how this can be helpful. I am running an ad to promote my Cornerstone Tips lead magnet. Once the form is submitted, the confirmation page includes encouragement to register for other lead magnets.

The result is that one registrant might subscribe for multiple things, which will lead to multiple reported registrations. By using First Conversion reporting, I can break this out…

In this case, we can make a reasonable assumption that about 427 unique people completed 533 registrations. While 533 total registrations is accurate, the 427 number provides more context regarding the true number of people that my ads inspired.

I’ve used First Conversion repeatedly to solve reporting problems just like this one.

Reporting Errors

It’s important to have knowledge of attribution and use the tools available to you to add important context. But there are times when reporting is flat-out wrong.

As much as advertisers want to blame Meta for flawed reporting, it’s almost never Meta’s fault. In some cases, it may require troubleshooting on your part.

1. Inflated results. Complaints of inflated results off come from an inability to match Ads Manager with third-party reporting. Your results can appear inflated due to remarketing or multiple conversions performed by unique customers. These results wouldn’t be inflated, but would require a closer look.

Otherwise, results can be inflated due to a conversion event issue. If Meta is reporting conversions that did not happen, it may be due to one of the following:

• Firing the event on the wrong page or prematurely
• Events from multiple sources are not deduplicated

In these cases, you need to test your events and check logs to pinpoint the problem.

2. Underreported results. Otherwise, you may find that Meta isn’t able to attribute conversions fully. This can be due to privacy/tracking issues, particularly since iOS 14+ (though many of these conversions are modeled now). Meta may also be unable to attribute a conversion because it falls outside of the attribution setting.

Reporting Holes

Even if you are knowledgable of how attribution works and you’re diligent about providing important context, I recommend that you fully embrace the fact that reporting will never be perfect. Ads Manager numbers will almost never match up perfectly with third-party reporting.

That’s not necessarily because Ads Manager is wrong or the third-party reporting is wrong. But there are important quirks that make 100% consistently virtually impossible. Beyond clear errors that lead to over or under-reporting, you should otherwise embrace these likely differences.

There are some very clear reporting holes that often lead advertisers on an endless chase to find answers…

1. View-through conversions. Unless there’s direct integration with Ads Manager, third-party reporting will not have any information about whether a person viewed your ad and did not click prior to converting. This is information that only Meta has and you’ll drive yourself crazy attempting to verify it.

2. Clicks that don’t drive traffic. It took me more than a decade to realize this, but click attribution does not require a click on an external link. While the vast majority of conversions resulting from a click may result from people clicking on the link in your ad, some may not. And that would mean UTM parameters become useless for this segment of click conversions, which are no different than view-through conversions when it comes to being able to verify them.

3. The 7-day purchase decision. The easiest conversions to verify are those that happen immediately: A person clicked your ad, was redirected to your website, and immediately converted. But that’s not always how it works. Some conversions, especially the purchase of higher priced products, can take multiple days following the first click. It can take customers across devices and browsers, potentially negating URL parameters.

And that assumes that the conversion happens within the 7-day attribution window at all. As mentioned above, you can often find hidden conversions that happened using the 28-day click attribution setting. But depending on what you’re promoting, the customer journey may be even longer. This makes attribution and measurement difficult.

Your Turn

If you understand Meta ads conversion results at this level, you’re ahead of most advertisers. Anything else you’d add?

Let me know in the comments below!

The post Meta Ads Conversion Results: A Guide appeared first on Jon Loomer Digital.

Meta made an insane number of changes to advertising in 2024, but there is plenty that could be enhanced. This post focuses on specific ways that Meta could further improve the ads product in 2025.

Missing from this list are some of advertisers’ biggest complaints regarding support, ad review, and scams. Those are structural problems without an easy fix.

This list also avoids requests for features that clearly conflict with the current direction of the product. We know that the future of Meta advertising is less control and more automation. The focus here is on finding ways to make that automation better.

In most cases, these are very specific feature requests. I’m no programmer, so I won’t claim to know how easy or difficult it may be to pull them off. But they would improve the product for Meta advertisers.

Let’s get to the list (in no particular order)…

1. Expansion Breakdown

Meta introduced Advantage Detailed Targeting (then called Detailed Targeting Expansion) in 2021. This allowed Meta to expand your audience and reach people beyond the Detailed Targeting inputs if it would result in improved performance.

Many advertisers revolted. I was among this group initially. It was the beginning of our loss of control.

Advantage Detailed Targeting is now on by default and can’t be turned off when the performance goal is to maximize conversions, link clicks, or landing page views. Advantage Lookalike will expand your lookalike audience when maximizing conversions.

Of course, that assumes that you use original audiences. The default targeting approach is now Advantage+ Audience, which treats most of your inputs as suggestions.

While an algorithmic expansion of your audience is not perfect, it is our reality. In 2025, we can expect we’ll further lose targeting control, not gain it back. We need to accept and embrace this.

One way that Meta could improve confidence in audience expansion is by adding a breakdown to reporting. Provide two rows:

• Results from audience that was explicitly targeted from inputs
• Results from audience that was reached beyond targeting inputs

This added transparency can show advertisers how audience expansion is helping them. They may even see that the cost per result is better for the expanded audience. Or not, but this is a necessary breakdown.

Of course, this isn’t a new request. I’ve asked for it from the beginning of audience expansion, and I’ll keep on asking.

2. Audience Segments and Ad Scheduling Availability

Meta added two great new features to manual sales campaigns in 2024…

The addition of Audience Segments was transformative.

It’s because of Audience Segments that I was able to run several tests that changed my opinions about targeting. But, there’s one problem: This feature should be available for all campaign objectives, not just sales.

Another feature added to sales campaigns in 2024 was Ad Scheduling.

Scheduling normally happens on the ad set level, but this allows you to schedule ads individually. This way, you can have ads run within the same ad set based on your promotional schedule.

Once again, it’s a great feature, but it’s only available for sales campaigns. Why?

Both features were originally made available for Advantage+ Shopping Campaigns before rolling out to manual sales campaigns, too. Maybe this is the natural progression and we’ll eventually get access for other objectives.

If not, it feels like an unnecessary restriction. There’s nothing special about sales campaigns that would make these features unique to them. They’d be just as valuable when using any of the other campaign objectives.

Until then, I find creative ways to use the Sales objective even when I don’t optimize for a purchase so that I can get access to Audience Segments. That’s how valuable this feature is.

3. Enhancements to Audience Segments

Audience Segments are awesome. They provide important context to algorithmic targeting by breaking down results into three groups:

• Engaged Audience
• Existing Customers
• New Audience

This helps us see how budget and results are distributed between remarketing and prospecting groups. But it can be improved in three specific ways.

1. Add a layer. Right now, you cannot define Engaged Audience using Facebook Page, Instagram Account, and video view custom audiences.

You can certainly make the argument that these are lower quality than the other custom audiences used to define your Audience Segments. But they do make up your remarketing.

Meta could either add these custom audiences to Engaged Audience or create a new one (“In-App Audience”) to give us additional information about algorithmic remarketing.

2. System generated. Something else Meta could do to make Audience Segments accessible to all advertisers is to auto-generate them initially. Meta has the data to create these without our input.

• Engaged Audience: All pixel activity
• Existing Customers: All purchase events

Customer list custom audiences are more complicated since you may need to segment the purchases from non-purchases, but the pixel gives Meta the initial data to generate these segments for us.

Advertisers could then edit these audience segments as necessary, but an initial definition could help expose more advertisers to the value of this tool.

3. Auto update. It’s not 100% clear if this is an actual problem or if I experienced a bug, but if it’s a problem it needs to be fixed.

I stumbled on an issue where it appears that website custom audiences stop updating if they haven’t been used in targeting recently. This is problematic if Meta wants us to trust algorithmic targeting (not use remarketing audiences) while leveraging audience segments (which rely on those same audiences).

Even if website custom audiences stop updating from a lack of activity (nothing in Meta’s documentation suggests this), it would be a simple fix. Define “activity” to include use in audience segments.

4. Address Advantage+ Audience Weaknesses

I use Advantage+ Audience when optimizing for a purchase, but there is potential for issues with this feature for any other optimization. If Meta can get more of the action that you want by going beyond your suggestions, it will.

That shouldn’t be a problem when optimizing for purchases. If Meta can get you more purchases by ignoring your inputs, that’s a means to an end.

But it can be an issue when optimizing for link clicks, landing page views, ThruPlay, post engagement, and even leads. The issue isn’t that Meta can go beyond your suggestions of custom audiences, lookalike audiences, and detailed targeting. The problem is related to age and gender.

When using Advantage+ Audience, both age maximum and gender are audience suggestions. They are not included in Audience Controls, which act as a tight constraint.

Again, this shouldn’t be an issue when optimizing for purchases. Advertisers can restrict their audience unnecessarily, which drives up costs. You may think that your target audience is women between the ages of 25 and 44, but if a 45-year-old man buys your product (possibly for their partner), that’s a good thing.

But this becomes a problem when optimizing for any other type of action. Let’s assume that you serve female entrepreneurs and 99% of your customers are women. But if you optimize for link clicks, landing page views, or engagement of any kind, your ads will be shown to men. Why? Because they will perform the action that you said you want.

Meta doesn’t care that they won’t eventually buy from you because that’s not the focus of the performance goal you chose. Meta will ignore your audience suggestions of gender and age limit.

I’ve seen this become an issue for leads, too, though it isn’t always. Meta can dedicate a high percentage of my budget on people 55+ because it results in cheap leads. But I’ve also found them to be low quality.

The way around this is to use original audiences, where age maximum and gender are tight constraints. But, this shouldn’t be necessary. Meta could make them part of Audience Controls when using Advantage+ Audience, too — or at least make them available when optimizing for something other than purchases.

5. Address Quality Issues with Optimization

Truthfully, the solution above is a Band-Aid on a much bigger problem. That solution also conflicts with what I said at the top — it’s a request for more control. We’re not going to get that.

The lack of control isn’t the central problem here. The more pressing issue is Meta’s inability to sort out low and high-quality actions. If you optimize for link clicks or landing page views, Meta will do all it can to get as many of them for you as possible. The algorithm is unconcerned about whether they come from accidental clicks or from people who are likely to buy from you.

This is not a new problem (I’ve covered it often), but it is magnified with algorithmic targeting. By removing the guardrails of targeting restrictions, the quality of the actions you get are likely to decrease.

It’s a problem that has solutions, if Meta cares about them…

1. Allow ability to prioritize quality actions. This concept isn’t new to Meta advertising. We already have the option of “maximize number” or “maximize value” when optimizing for purchases.

We could also have options of “maximize number” or “maximize quality” of link clicks, landing page views, post engagement, video views, and more. For example, Meta could prioritize landing page views that resulted in more time spent, return visits, and conversions performed. Quality actions would cost more, but it’s a trade-off most advertisers would take.

2. Change Meta’s signals. Of course, Meta could just update their signals to begin with and prioritize quality actions.

3. Incremental conversions. We know that Incremental Conversions are in testing, and I don’t anticipate that this will apply to many of the actions discussed here. But you could make the argument that Meta could find a way to apply this or a similar concept to top of the funnel actions.

6. Organic Conversion Reporting

It baffles me that this isn’t a thing…

Ads Manager reports on all conversions performed by people you paid to reach. This is logical. But it doesn’t reflect the total impact of your ads.

What happens when someone you paid to reach shares your ad? Someone you did not pay to reach may buy from you. This person would not have converted without the existence of your ad, yet the ad won’t receive any credit.

I’m not suggesting that Meta lump organic in with paid conversions. That would be potentially misleading. But Meta could provide a breakdown of Paid vs. Organic to provide a more complete picture of your ad’s impact.

This could extend beyond Ads Manager, too. If Meta has your pixel and event data, there’s no reason why they couldn’t provide some basic conversion reporting with your organic insights. Instead, all we get is information like impressions and link clicks. Meta could surface the conversions, too.

Once again, this is not a new request. I’ll keep asking it.

7. Address Click Attribution Issue

I stumbled on a troubling discovery in late 2024 that forced me to question what I previously believed to be true: Click attribution doesn’t require a click on an outbound link.

There are two ways Meta can give credit to an ad for a conversion…

Click Attribution: Someone clicked on your ad and converted within seven days.

View Attribution: Someone viewed your ad, did not click, and converted within a day.

Up until very recently, I believed that click attribution required a click on a link to your website. It was logical. If they did not, that could be counted as a view-through conversion.

But since click attribution includes any click, reporting gets fuzzier. Advertisers already have trouble with conversion numbers matching up between Ads Manager and third-party sources. While UTM parameters can help when people click on outbound links, they are worthless for this case.

That’s why I’ve always lumped this type of conversion in with view-through attribution. Your ad may have contributed to the conversion, but the value isn’t as clear as when someone clicks an outbound link and converts.

It took me a decade to realize this, but these lower-quality click conversions are lumped into your click conversions. There’s no way to separate them.

I realize I’m way behind on this request since it’s not a new problem, but there are two things that Meta could do:

1. Move these conversions to view attribution. This solution squares with my initial interpretation of click attribution, so it’s my preference. I believe strongly that these should not be counted among click attributed conversions.

2. Create a separate attribution. This adds complexity, so it’s not ideal. But Meta could conceivably break this type of conversion off into it’s own group: “In-App Click.” That way we could see how many of our click conversions didn’t come from an outbound click. You could even turn it off at the ad set level.

8. A Better, Smarter Event Setup Tool

I can’t tell you exactly when Meta introduced the Event Setup Tool, but it’s been around for several years. It’s also been untouched by enhancements since it’s initial rollout.

It’s still buggy. It’s still painfully limited. But it also holds a ton of promise if Meta chose to focus some development on it.

Meta may need to start over to make this tool more useful, but it would be worth it. It could become the primary way advertisers set up and manage their pixel events.

Right now, Meta relies on third-party integrations for the vast majority of pixel and event management. This creates confusion for advertisers since there isn’t one clear way of managing it. It doesn’t need to be this way.

Meta could develop a smarter, more streamlined and integrated tool that detects events and helps you set them up easily. This also does not need to be limited to standard events — it could help you set up custom events as well.

The Event Setup Tool now is manual, slow, and limited. Instead, Meta could offer an auto-detection of events that you can approve. The technology for auto detection of events already exists.

I’m not a designer or programmer, so forgive me if my vision of how this would work isn’t crystal clear. But this is one of many examples where advertisers are forced to use third-party solutions when it shouldn’t be necessary.

9. Smarter Creative Enhancement By Placement

We’re headed in this direction, but we’re not there yet. It may be the most likely improvement on this list to become a reality.

Currently, advertisers are asked to provide three different versions of ad creative when uploading images and videos.

These different aspect ratios are used for different placements. Of course, this system is imperfect because the sizes Meta requests aren’t always consistent with what is recommended in official documentation.

It would be a whole lot easier if advertisers could upload a single creative that Meta adjusts automatically (and productively) for other placements. While you could approach this level of simplicity with a carefully created 9:16 image or video, this could apply to other dimensions as well.

Submit a square image and Meta uses AI to adjust and generate the background where necessary. This exists now, but it’s in testing and not applied in all situations.

Meta could simplify this by skipping the request for three versions. After submitting a single image or video, Meta then presents the versions that were generated using AI and smart cropping.

While most of my feature requests require new development, this feels more like better presenting and utilizing functionality that already exists.

Your Turn

What other features could Meta develop to improve the ad product in 2025?

Let me know in the comments below!

The post 9 Ways Meta Can Improve Advertising in 2025 appeared first on Jon Loomer Digital.

Meta will impose new restrictions on customer list custom audiences in 2025. Does this apply to you? What should you do?

Let’s get to it…

Whom Does This Apply To?

These restrictions apply to advertisers using customer list custom audiences to promote the following categories:

• Housing
• Employment
• Financial Products and Services (including Credit)

In other words, all of the Special Ad Categories other than Politics, Elections, and Social Issues. Restrictions apply to advertisers based in the US or reaching audiences in the US.

Sharing of Customer List Custom Audiences

The new restrictions apply to the sharing of customer list custom audiences for these classes of business. There are two situations considered:

1. Sharing between ad accounts within the same Business Portfolio.

You will be able to share customer list customer audiences with other ad accounts within the same Business Portfolio (the new-er name for Business Manager) as long as all people with permissions to manage ad campaigns have the same business email domain.

And no, using Gmail, Yahoo, and other generic email domains won’t get around this restriction.

It’s not clear if this is the complete list, but the assumption is that you will use email domains that prove you work for the same employer.

2. Sharing between ad accounts across different Business Portfolios.

You will not be able to share customer list custom audiences in this case, regardless of the email domain. Both ad accounts need to be within the same Business Portfolio.

Meta provides the following examples for ad accounts within the same Business Portfolio…

The first column of email addresses represents all people within an ad account that will share the customer list custom audiences who have permissions to manage ad campaigns. The final column represents those who would receive that audience.

The first example is acceptable because all people within both ad accounts have the same email domain. The second is not because one person within the sharing account who has access to manage the ad campaigns uses a Gmail domain.

Consumer Reporting Agencies

Consumer reporting agencies (CRAs) are not allowed to use any customer list custom audiences, including their own, for targeting. CRAs collect and sell financial and credit information about people.

Yeah, that would be bad in this case. Meta doesn’t want advertisers to discriminate and these lists could be used to do exactly that.

Additional Certification

Beginning in January of 2025, advertisers will begin to see a new certification requirement for customer list custom audiences.

The main points:

1. They are not a consumer reporting agency, nor did they receive the information from one.

2. The audience isn’t based on sensitive information that shouldn’t be used for targeting.

3. They will follow Meta’s advertising policies.

Enforcement Timeline

If you use customer list custom audiences in these categories, here’s the timeline of how enforcement will rollout…

January 2025

New campaigns must use customer list custom audiences that fall within the guidelines mentioned above or you may not be able to publish them. If you published campaigns prior to these new restrictions, they will continue to run, but you may not be able to edit them.

March 2025

Campaigns that were published prior to restrictions that do not follow these guidelines may be paused.

Why is This Happening?

Meta has faced a lot of heat over the years for advertising that falls within sensitive topics. This is why Special Ad Categories exist in the first place.

The Special Ad Category designation is meant to protect the advertiser (and Meta) by preventing them from using discriminatory targeting. Audience selection looks like this:

1. Postal or zip code selections are unavailable
2. Minimum of a 15-mile radius around a location
3. 18-65+ with no ability to limit by age minimum or maximum
4. No ability to limit by gender
5. Some sensitive detailed targeting options are removed

Since these restrictions exist, it’s no surprise that advertisers may attempt to get around them by using custom audiences. They could assemble a list of people who are all within a certain age group or neighborhood. This would violate terms for these Special Ad Categories.

I’m actually surprised Meta doesn’t simply remove the ability to use customer list custom audiences in this case. It would be much easier. But since they haven’t, they’ll need to add more restrictions to make sure that advertisers know the rules and follow them.

The sharing of custom audiences also falls into a bit of a gray area anyway. I’ve long interpreted the rules to mean that you can only target people who have explicitly given you the right to contact them. To a point, these restrictions wouldn’t be necessary if they are interpreted that way by everyone.

What Should You Do?

First, investigate whether this applies to you. Do you run ads for a business that fall in the categories of housing, employment, or financial products and services? Are you or the client in the US?

If so, check your alerts for warnings related to these restrictions. I assume you’d see them on the Audiences page, but you may also see something on Account Overview.

Next, do you share customer list custom audiences for these businesses? If not, this isn’t really an issue.

Finally, consider whether all advertisers on an ad account utilize the same email domain. It’s quite possible they don’t since it’s surely common that advertisers would use “generic” email domains like Gmail. You’ll need to get that corrected, which would likely be a bit of a hassle.

Your Turn

Do you run ads for businesses that fall under these categories in the US? How have you prepared?

Let me know in the comments below!

The post Restrictions on Customer List Custom Audiences appeared first on Jon Loomer Digital.

No matter how much experience you have as a Meta advertiser, expect to learn something new that surprises you to the point of questioning many of the things you once believed about them. Put Meta click attribution into this category.

I started this website in 2011. I’ve written and educated others on the topic of Facebook — and then Meta — advertising since 2012. I make it my responsibility to know every nuance on the topic as well as one could reasonably expect to know it. And yet, here we are.

Meta click attribution — how Meta gives credit for a conversion after clicking an ad — does not work entirely the way I’ve assumed it did for the past decade. If that’s true for me, it’s likely to be a surprise for you, too.

Meta’s documentation on click attribution is ambiguous. It’s easy to make assumptions based on what it does and does not say. It wasn’t until I ran a test that I have clarity on what it actually means.

I am certain that I am part of the majority who misunderstands click attribution. The confusion matters. This is surely the source of many of the reporting complaints that advertisers have.

In this post, I’ll cover the following:

• Click attribution and how I assumed it worked
• Meta’s documentation and a lack of clarity
• A test for confirmation
• Why this matters

Let’s go…

Click Attribution and How I Assumed it Worked

Attribution is how Meta gives credit for an ad. By default, Meta reports a conversion if it happens within 7 days of clicking or 1 day of viewing your ad without clicking.

View-through conversions are the source of the most controversy. In this case, Meta can give an ad credit for a conversion even though the person never clicked it — assuming they converted within a day of the ad impression.

Click-through felt a bit more straight-forward. These are people who clicked your ad and went to your website. They may not have converted immediately, but that conversion happened within seven days. Your ad very clearly contributed to that conversion.

View-through conversions are a reporting black hole. Only Meta knows whether a person was shown your ad, didn’t click, and then converted within a day. It’s very difficult to prove or disprove.

Click-through conversions reported in Ads Manager will not always match up with third-party reporting, but they should typically be close. You can use UTM parameters to help give reporting tools more insight into whether customers came from your ad. You could also use 1-day click attribution, which should help limit cross-device and multiple-session visits.

Click attribution is more dependable and easier to back up with other reporting because it requires a click from your ad to your website (or so I assumed). Any differences in reporting could generally be explained by the complicated journey that can happen over a seven-day period.

Meta’s Documentation and a Lack of Clarity

Click attribution first became my focus about a month ago when an astute reader asked me whether click attribution required an outbound click on your ad to your website. I reflexively replied that it did.

But I wanted to cite official documentation so that it didn’t seem as though I were making it up. The problem was that I couldn’t find any such clarity.

I went through page after page of Meta’s documentation on attribution. Nowhere was it clearly stated that click attribution requires a click on an outbound link on your ad. It also doesn’t say that it could be any click — clicks on images, videos, reactions, comments, or something else. It’s completely ambiguous.

Because of this ambiguity, I wasn’t ready to disregard what I believed to be true based on more than a decade of experience on the topic. But I also didn’t want to continue believing it blindly.

A Test for Confirmation

This situation was primed for a test. Meta might not be clear about what they mean by click attribution, but a strategically-run test could prove it.

Does click attribution include all clicks that result in a conversion, regardless of whether someone clicked an outbound click on my ad? In order to know for sure, we’d need to eliminate the outbound click option.

I created a campaign using the Engagement objective with the following conversion location settings:

• Conversion Location: On Your Ad
• Engagement Type: Post Engagement
• Performance Goal: Maximize Daily Unique Reach

Targeting isn’t particularly relevant, but I wanted to be sure to reach a highly engaged audience who would be excited to participate in my experiment. So, I used original audiences and targeted people who were engaged on my email list during the past month.

To keep this simple, I used only the Facebook feed placement. I didn’t want to worry about versions and quirks by placement.

Here is my ad:

The primary text did not include a URL. I made it clear that I was running an experiment and asked people to follow the instructions in the image.

They were asked to do the following:

1. Click the image
2. Open a browser tab
3. Go to jonloomer.com/experiment
4. Follow all instructions on that page

I asked for the click to make click attribution possible. I didn’t include the URL in text so the link itself could not be clicked.

When they went to that page, people were asked to click a button.

Once that button is clicked, a confirmation page loads and a custom event unique to this experiment (the custom event is called “experiment”) fires.

Test Results

If click attribution worked the way I originally assumed, the only conversions that Meta could report would be view-through. If someone viewed my ad, didn’t click an outbound link on my ad, and then converted within a day, that falls within my preconceived view-through definition.

But if click attribution doesn’t require clicks on an outbound link, we will know that immediately by comparing attribution settings. If there’s even one conversion reported using 1-day click, it’s clear evidence that an outbound click isn’t required.

It didn’t take long to get confirmation.

Meta attributed 33 conversions using the “Experiment” custom event. All 33 were the click-through variety.

This is convincing evidence, if not proof, that click attribution does not require a click on an outbound link.

Why This Matters

I’m not going to lie. This shook me.

For years, I was confident that click attribution required a click on an outbound link. And why wouldn’t it? If someone converts without clicking an outbound link, we already have a category for that: View-through conversion.

We know that view-through conversions are a reporting black hole. If you have huge reporting discrepancies between Ads Manager and GA4 or other third-party reporting software, the problems typically start there.

But now I’ve learned that many of the conversions that I’ve long believed to be view-through are actually falling into the definition of click attribution. And while view-through conversions are limited to a one-day window, these conversions can happen within seven days.

Your 7-day click conversion numbers consist of people who clicked the link in your ad. But they could also include people who made other clicks — on your image, video, comments, reactions, and more. If they convert within seven days, they’re counted.

Counting these conversions isn’t necessarily the problem. The issue is that you can’t separate the click conversions that happened from clicking an outbound link (the most valuable conversions) from those who clicked something else.

This will matter most when remarketing. Someone who is on your email list gets served an ad impression. They may “like” it simply to show appreciation. They get an email within seven days that they act on. The ad that was “clicked” then gets credit for a conversion.

I would normally say to mostly ignore view-through conversions when remarketing. They aren’t nearly as valuable as when reaching a cold audience — someone who would need to take steps to find your product again to complete the conversion.

But this tells me that it’s impossible to completely ignore view-through — and other conversions that don’t require a click on a link. Your numbers are likely to be inflated.

This also matters for those wanting to confirm their results. UTM parameters will not help you confirm this type of click attribution. Like view-through, you’ll need to take Meta’s word for it.

That leads to reporting discrepancies and frustration.

How Common Is It?

One question I have that is difficult to answer is regarding how often this type of conversion happens in the first place. We’re likely dealing with an extreme minority of reported conversions in most cases. And really, this is a big reason why I was oblivious to these conversions in the first place.

But there are a couple of factors involved…

1. Do you feature a link?

The typical static link ad provides very few options for clicking that don’t result in a click to your website. This includes carousels. If you click anywhere on the creative area of an ad, you’ll be redirected to a website.

There remain other clicks, of course. But then you’d need a scenario where someone from a cold audience “likes” your ad and then Googles you later. Granted, I saw this as a view-through conversion before, but it shouldn’t make up a large percentage of your click conversions.

2. Do you run remarketing campaigns?

Remarketing results are already likely to be inflated if you aren’t careful. Whether it’s ignoring view-through conversions or using 1-day or 7-day click attribution in the ad set, there have been ways to add context so that you aren’t misled by inflated numbers.

But now I’m seeing that it’s even more difficult to control these inflated numbers than I thought. You could ignore view-through conversions. But if you target people who receive your emails, visit your website regularly, or simply would have converted without seeing your ad, your are likely to reach people who click without clicking through to your website.

When that happens, you are likely to assume that they clicked through. But it will be impossible to know for sure. And Meta’s optimization will go after more of these people to get you the results that you want.

What Meta Must Do

First, Meta needs to clarify their documentation on attribution. It can’t be ambiguous. The definition of click attribution should specify that it includes all clicks, not just clicks on outbound links. Don’t let anything be assumed or it will seem deceptive.

But that’s not enough. We need more clarity in reporting. Meta provided this with engaged-view attribution. It tells us that while a conversion didn’t result from a click, the person watched your video for at least 10 seconds before converting.

We need something similar for click attribution. Otherwise, it’s impossible to separate those who actually clicked through from those who didn’t. Not only does that result in misleading reporting, but it can pollute Meta’s optimization.

How You Should Approach This

There isn’t much we can do differently as advertisers in response to this information. But it can provide important context that we can use to better understand the chaos of results.

Your results will never match up with third-party data. You can use UTM parameters and various tools that claim to fill in the blanks, but there will always be unexplained discrepancies.

Know why these discrepancies exist. Know that it’s because of view-through conversions, cross-device conversion journeys, and tracking limitations. But also know that even if you isolate click attribution, there are likely to be conversions that didn’t result from a click on an ad to your website.

We simply need to accept that and convey that guarantee of uncertainty to clients.

Your Turn

What are your thoughts on how click attribution works?

Let me know in the comments below!

The post Uncovering the Reality of Meta Click Attribution appeared first on Jon Loomer Digital.

It is highly likely that you are using ad creative that fall outside of Meta’s recommended aspect ratios. You would be forgiven if this is the case since Meta’s own process for uploading images and videos all but assures that this will happen.

Of course, it will take some additional work to accomplish the goal of providing optimally sized images and videos for your ads. But this post will help highlight precisely what you need to do for that to become a reality.

I recorded a short video about how Meta recommends a 4:5 aspect ratio for many of the placements where you’re likely using 1:1. But, it’s not quite that simple. The recommended aspect ratio often depends on whether you are using a video or a static image.

Let’s clear up any confusion so that you can use optimally-sized creative going forward.

Aspect Ratio Grid

Let’s jump right to the most important resource that you’ll want to save for later.

Placements are listed in the “placement groups” that are created when uploading your creative in Ads Manager (we’ll get to that in a minute). On the right are Meta’s actual recommended aspect ratios for videos and static images in those placements.

Those recommendations often conflict with the aspect ratios that Meta requests when assigning placement groups.

Creative Upload Confusion

When you create your ad, Meta attempts to simplify the process of creative upload by asking you to provide three different variations:

• 1:1
• 9:16
• 1.91:1

When you do this, Meta automatically assigns those variations to different placement groups.

• 1:1 for Feeds, In-stream ads for videos and reels, Search results
• 9:16 for Stories and Reels, Apps and sites
• 1.91:1 for Right column, Search results

This would be great if these placement groups were consistent with Meta’s own recommendations, but they’re often not.

Recommendation Sources

There are a few resources that I relied upon when creating my grid.

1. Aspect Ratios Supported By Placements in Meta Ads Manager

It was this table that got my attention in the first place. It highlights both the accepted and recommended aspect ratios for each placement. Here’s an example of what it looks like…

2. Placement Previews

What’s interesting is that most of the recommendations in the table above are consistent with what Meta recommends in placement previews. Here’s an example for Facebook Feed.

Meta recommends 4:5 for both images and videos in the Facebook Feed even though advertisers are asked to upload 1:1 creative for that placement during the ad creation process.

3. Best Practices for Aspect Ratios

This resource is a bit less detailed than the table, but it helped answer some questions when I was seeing conflicting information.

4. Format Specs & Recommendations

This resource covers quite a bit more beyond creative aspect ratios, and the recommendations aren’t always explicit. But this is how I came up with the 1:1 recommendation for right hand column. While the table mentions it as an option, this resource actually recommends it.

Conflicts

You’ll see this within the grid at the top of this post, but let’s summarize the conflicts that I found. Most of the conflicts are for videos, particularly within the placement group that Meta assigns 1:1.

While the aspect ratios that Meta asks you to create will still work, these are the cases where they may not be the most optimal…

Facebook Feed: Meta recommends 4:5 for both videos and images (1:1 upload requested)

Facebook In-Stream Videos: Meta recommends 16:9 or 4:5 videos (1:1 upload requested)

Ads on Facebook Reels: Meta recommends 9:16 videos (1:1 upload requested)

Facebook Marketplace: Meta recommends 4:5 videos (1:1 upload requested)

Facebook Profile Feed: Meta recommends 4:5 videos (1:1 upload requested)

Facebook Video Feeds: Meta recommends 4:5 videos (1:1 upload requested)

Instagram Feed: Meta recommends 4:5 videos (1:1 upload requested)

Instagram Explore: Meta recommends 4:5 videos (1:1 upload requested)

Instagram Explore Home: Meta recommends 4:5 or 9:16 videos (1:1 upload requested)

Instagram Profile Feed: Meta recommends 4:5 videos (1:1 upload requested)

Facebook Business Explore: Meta recommends 4:5 videos (1:1 upload requested)

Facebook Search Results: Meta recommends 1:1 videos (1.91:1 upload requested)

Facebook Right Column: Meta recommends 1:1 for both videos and images (1.91:1 upload requested)

How to Customize by Placement

Now that you have a guide for which aspect ratios to use for each placement, let’s discuss how you’ll execute it.

1. When you upload your creative at the start, your approach will be different depending on whether you are using videos or images. If videos, provide 4:5, 9:16, and 1:1 for the initial placement groups. If images, provide 1:1, 9:16, and 1:1.

2. Now you will need to customize your creative by placement. Let’s assume that you are using an image and uploaded a 1:1 version for one of the placement groups. That will satisfy Meta’s recommendations for almost all of the feed placements, except for Facebook Feed.

Within the Media section, expand the Feeds group. Then hover over Facebook Feed and click the “Edit” icon.

On the left, click to change the media for the selected placement.

Once you upload and select a new image, an icon will appear indicating that you’ve made a customization to that placement.

You will then need to repeat this for every placement where there’s a conflict. You may even choose to provide a mix of images and videos for a single ad, depending on the placement. That will require a reasonable amount of work, but you may find it worthwhile if an improvement in performance follows.

Your Turn

Everything in this post is subject to change, of course. My hope is that Meta will change the initial upload process so that the requested aspect ratios are consistent with their recommendations. Until then, you’ll need to do a bit of manual work.

Are there any other conflicts that I missed? Let me know in the comments below!

The post Recommended Aspect Ratios By Placement for Meta Ad Creative appeared first on Jon Loomer Digital.

There was a time when the majority of my ad budget was spent on remarketing in one form or another: Website visitors, email list, followers, post engagement, and more. I’ve abandoned much of this in favor of Meta’s algorithmic targeting, but there are exceptions.

There are times when remarketing continues to make good, smart sense.

Don’t misunderstand my intent. I still think advertisers use remarketing far too often. It’s not only less effective than it once was (and advertisers often misinterpret the effectiveness of their remarketing results), but it’s also often unnecessary.

Let me explain…

Why Remarketing is Mostly Unnecessary

Don’t confuse the message here. Reaching people who are most closely connected to your business remains valuable.

One of the primary reasons that a separate remarketing ad set is mostly unnecessary now is that algorithmic targeting will prioritize these people anyway. When using Advantage+ Audience, Meta prioritizes conversion history, pixel data, and prior engagement with your ads.

You can prove this with the help of audience segments. I’ve seen repeatedly that Meta spends in the range of 25 to 35 percent of my budget on my existing customers and engaged audience (those who are on my email list or have visited my website, but who haven’t yet bought from me).

Here’s an example, using Advantage+ Audience without suggestions…

I’ve also seen this when using original audiences going broad…

Here’s an example using two different ad sets: One using Advantage+ Audience without suggestions and one using only remarketing.

When using Advantage+ Audience without suggestions, Meta spent 45 percent of my budget on the same people that I otherwise targeted specifically in a separate ad set. By giving the algorithm more freedom, I found that it maintained a more reasonable frequency compared to when I only targeted the remarketing group.

Meta now combines remarketing and prospecting to create an optimal balance. It will otherwise be more expensive to reach your remarketing audience (which tends to also be the most likely to perform the action that you want), but the prospecting group is larger and cheaper.

For this reason, general remarketing (where you target broad groups of website visitors, email list, and people who have engaged with your page) is rarely necessary now. It happens automatically.

Misinterpretation of Results

I should also point out that one reason some advertisers continue to swear by remarketing is a misinterpretation or misunderstanding of their results. Whenever I see someone share conversion results or ROAS that seem too good to be true, it’s often because the results are inflated.

To be clear, remarketing results should be good. But they will also be inflated. This is a great opportunity to break down your results and test how good they actually are.

Use the Compare Attribution Settings feature and break down your results by attribution setting. It would also be good to use First Conversion reporting (or at least both First Conversion and All Conversions).

When remarketing, you can expect a disproportionately high concentration in the 1-Day View column. That’s usually because of two different scenarios:

1. You emailed people on the same day they were shown your ad.
2. Regular website visitors happened to visit on the same day they were shown your ad.

It doesn’t necessarily mean that the ad didn’t do anything. In some cases, these customers saw it and it contributed to their buying decision. But a very common scenario is that they didn’t even see your ad. They would have made the purchase anyway.

View-through conversions are much more valuable when they come from new customers. They saw your ad or were impacted by it, but they didn’t click it. They remembered the product or brand and Googled you later. Then they made a purchase.

But when remarketing, at least a decent number of the view-through conversions are fluff.

When Remarketing Makes Sense

While remarketing is often unnecessary, there are some exceptions where it remains relevant.

Here are a few to consider…

1. A specific message for a specific group of people.

The most common example is an abandoned cart scenario. You want to show a different ad to people who have recently added your product to their cart but haven’t purchased. You may want to offer a discount to incentivize the sale.

Of course, it’s debatable whether this is necessary. Meta should prioritize people who have added to cart when determining who will see your ads. It will be more expensive to isolate those people in a separate ad set. It’s worth testing.

I’m actually using a variation of this right now. I have a special offer, but I only want a very specific segment of my email list to see it. While it’s open to the public, my preference for this higher-value offer is people who have bought from me before.

In this case, I am targeting the same people I am emailing about this offer. I even refer to the email in the ad copy.

With this approach, I understand that the ad is only part of the sales pitch. Since it’s a high-dollar commitment, I’m hoping that it will help motivate these people to complete the sale.

I know that my ads will only be partly responsible for the conversions that are reported in Ads Manager. But my hope is to optimize the total number of sign-ups. Since the audience is small, the total amount of ad spend will be reasonably small, too. And since the sticker amount is about $1,000, it’s a low-risk approach that makes sense.

2. Low budget and a challenge to get results.

You’re trying to sell a high-dollar product, but you’ve only been given $50 or less of budget per day. You don’t have the option of building leads and need to go straight to the sale. Remarketing should be an option.

Yes, remarketing will happen naturally if you target more broadly. But maybe the remarketing audience is relatively small. Regardless, you may struggle to achieve meaningful results.

Remarketing doesn’t guarantee results here, but it’s at least a lower-cost option.

3. Top of funnel optimization.

Optimizing for link clicks, landing page views, video views, post engagement, or anything other than a conversion can be problematic. It’s even more so when algorithmic targeting is at play because Meta will do all it can to find you the cheapest action that you want. This is often at the expense of quality. By remarketing, you can limit your audience to people you’ve already determined are higher affinity.

I’ve done this when promoting my blog posts or Reels. I know that I’ll get lots of low-quality clicks or plays if I allow the algorithm to search out anyone to engage with them. But if my goal is to get more of the people who have already proven to engage with my content, I will isolate them with a custom audience.

Beware of Soft Remarketing

While remarketing still has its place, there’s a specific strategy that you should avoid and it goes like this…

1. Run an ad that optimizes for link clicks, landing page views, or video views.

2. Create an audience of the people who engaged with the first ad.

3. Target the people who engaged with the first ad.

The reason this is problematic is the issue we’ve already discussed about top-of-the-funnel optimization. If you optimize for link clicks, landing page views, video views, or just about any other action other than a conversion, you can expect low-quality activity. You are creating a custom audience of low-quality activity. And then you are remarketing to a low-quality audience.

If you’re going to use remarketing, be sure that you’re actually targeting a high-quality group of people. Investigate how that audience was created in the first place. Organically-generated audiences or those built when optimizing for conversions will typically be your best bet.

Let Algorithmic Targeting Do Most of the Work

Remarketing still has its place, but you should allow algorithmic targeting to do the heavy lifting — especially when optimizing for purchases. “Algorithmic targeting” doesn’t only include going broad or using Advantage+ Audience. It includes any situation where your audience is expanded (and that covers a high percentage of our inputs now).

Broader targeting should take up the bulk of your ad spend. While remarketing zeroes in on the people who are already close to you, there’s limited incremental lift. You also want to bring in new people who would have never bought from you if not for your ads.

Remarketing is a good short-term, low-risk play. Broader targeting is a slower, long-term play that will help assure you have a remarketing audience to reach in the future.

Your Turn

Do you still use remarketing strategies? What specific examples of remarketing success or challenges can you share?

Let me know in the comments below!

The post 3 Times You Should Prioritize Remarketing Over Meta’s Algorithmic Ad Targeting appeared first on Jon Loomer Digital.

Complaints about Meta’s algorithmic targeting are mostly misguided. Meta’s ability to find the people who are most willing to perform your desired action is extremely effective. But there is a fatal flaw that impacts optimization for any event that isn’t a purchase event.

Before you come at me about the issues with algorithmic targeting, I get it. I say that it’s “effective” because it’s efficient at doing exactly what it’s supposed to do. The flaw prevents it from being far more valuable.

Some advertisers will spend without seeing it. They see the results and don’t ask questions. Others will reject algorithmic targeting entirely without understanding why they aren’t getting the results that they desire.

There is a problem that is frustratingly difficult, if not impossible, for advertisers to solve. It’s Meta’s problem to fix, and I’ve been complaining about it for years.

I know, I’m being cryptic. It’s not easy to explain in an opening paragraph.

Let’s back up…

Who Sees Your Ads?

First, it’s important to understand that the definition of “targeting” has changed. I’d say that this evolution is part of what confuses advertisers. We don’t know how to communicate what “this” is now.

Not long ago, I asserted that targeting was the most critical factor to the success of your ads. Good ad copy and creative couldn’t recover from a bad targeting pool.

Of course, our inputs are only kinda sorta considered now when it comes to the audience that sees our ads.

1. Advantage+ Shopping Campaigns allow for virtually no targeting inputs at all. No detailed targeting, lookalike audiences, custom audiences, or much of anything.

2. Advantage+ Audience is the default option for defining your audience now. You can define a few things like location and age minimum, but your inputs are otherwise seen as suggestions (and it’s questionable how much they’re considered at all).

3. Original Audiences tend to be the fall-back for advertisers who want to retain targeting control. But, most don’t realize that their audience is usually expanded, especially when optimizing for conversions.

The primary lever that controls who sees your ads is the performance goal.

If you’re able to strictly define your audience (which is rare), Meta will find the people within that audience who are most likely to perform the action that you want.

If your inputs are seen as suggestions, your audience is expanded, or you don’t provide any inputs at all beyond the basics, Meta will find those people within the largest pools of people.

Is this targeting? Not really. It’s providing some initial suggestions and constraints and defining what you want so that Meta can find the people who will lead to results.

Like I said at the top, Meta is actually very good at this. Fewer constraints will almost always lead to more and cheaper results. But, that’s not without some problems.

When Optimization is Most Effective

Meta is best at generating high-quality results with minimal guidance when you are able to clearly articulate what you want. There are three primary examples of this…

1. Maximize Conversions (Purchase Event).

This requires that you’ve set up conversion event tracking and have defined purchase events. Meta will focus on getting you the most purchases within your budget.

2. Maximize Value (Purchase Event).

This requires that you pass value with your purchase events and have a variety of purchase prices. You may get less volume of purchases in this case, but Meta will focus on generating the highest Return on Ad Spend.

3. Maximize Conversion Leads.

Conversion Leads optimization is possible when using instant forms and requires several months of setup to define your funnel. Meta will then optimize to show your ads to people who will most likely become high-quality leads.

It doesn’t mean that you’re guaranteed to get great results when using any of these three approaches (so many factors contribute to that). But these are the times when you and Meta are on the same page regarding what you want.

Where Optimization Struggles

The reason the above three approaches to optimization work is that there is agreement over what a quality result looks like. You’ve defined that you want more purchases, more value, or more conversion leads, and Meta will focus on getting you those things. If successful, there shouldn’t be a dispute about the quality of those results.

Where this goes wrong is when using virtually any other performance goal. It includes some performance goals that are notorious for quality issues:

• Link Clicks
• Landing Page Views
• ThruPlays
• Post Engagement

But it can also include conversions that don’t result in a purchase. If you choose the performance goal to maximize conversions and select Lead or Website Registration as your conversion event, you likely run into a regular battle.

In all of these cases, you’ve only begun to define what you want. But you and Meta aren’t going to be on the same page.

If you choose to maximize link clicks or landing page views, Meta will focus on getting you as many link clicks or landing page views as possible. But you want quality traffic, not just any traffic.

If you maximize ThruPlays, Meta will show your ads to people most likely to watch at least 15 seconds of your video. But, that’s going to include people who are forced to watch your video. You want quality views of people who choose to watch, not just any views.

If you maximize conversions where the focus is on leads, Meta will try to get you as many leads as possible. But you want quality leads who are likely to buy from you, not just any leads.

In each case, Meta doesn’t care at all about quality. The algorithm’s only focus is on getting you as many of the action that you said you want.

This has always been an issue. But it’s less of an issue when you can tightly define your audience. When you can’t, Meta has fewer constraints to find results — and the likelihood for quality issues increases.

Exploited Weaknesses

This is the perfect storm for quality issues.

1. An inability to strictly define your audience.
2. An inability to define a quality action.
3. Weaknesses that can help Meta generate a high volume of the actions that you want

Understand that Meta’s delivery algorithm knows where to look to find the action that you want. This isn’t always good.

This can be as simple as going after people who are likely to act because they’ve visited your website or engaged with your ads. It can also be going after people who have engaged with similar products or businesses.

But, it can also be due to weaknesses that are exploited to get you more results.

1. Placements.

If you choose a performance goal to maximize link clicks or landing page views, expect that a large percentage of your impressions will be focused on Audience Network. Meta knows that it can get clicks there. It’s not clear whether these are from accidental clicks, bots, or click farms (before they’re detected), but you can bet you’ll get lots of low-quality clicks.

If you choose to maximize ThruPlays, a large percentage of your impressions will go to placements where people are forced to watch at least 15 seconds of your video. Audience Network Rewarded Video, which incentivizes people to watch videos in exchange for virtual currency or something else of value, is notorious for this. I’ve had cases where I’ve had more ThruPlays than people reached for this reason.

2. Countries.

If you target multiple countries at once and there’s an imbalance of cost to reach people in those countries, you may then see an imbalance in distribution. Especially if you choose to maximize top-of-the-funnel actions, Meta will try to get you the most actions possible within your budget. While this doesn’t guarantee lower quality results, it can be a contributing factor — particularly when a country is known for bots and low-quality accounts.

3. Ages.

If you aren’t able to restrict by age, this can be a weakness that will be tapped to generate more results. I can only speak from personal experience on this, but it seems that older people are much more likely to click on and engage with ads. But that doesn’t mean that they are a likely customer. If you are generating a high number of low-quality leads, it’s possible that Meta is focusing impressions on older people because it’s leading to more results.

4. Genders.

Let’s say that your business caters to women. In theory, you may not need to limit your audience when maximizing conversions when the conversion event is a purchase. The algorithm will try to get you more purchases and should adjust when men don’t buy.

But that’s not the case if you optimize for link clicks, landing page views, post engagement, or ThruPlays. Even though they may not be your target customer, men may engage at a high rate. And that will lead to low-quality results.

5. Low-Quality Accounts.

This is a big bucket that includes bots (before they’re detected), spam accounts, and real people who want to click on everything. If they perform the action that you’ve defined in your performance goal, these are going to be some of the primary people who see your ads. They’ll get you a bunch of cheap results, but that doesn’t mean those results are the quality that you desire.

NOTE: These five weaknesses aren’t nearly as big of an issue when optimizing for conversions when your conversion event is a purchase. The reason is that if it doesn’t lead to the action that you want (a purchase), the algorithm adjusts. But this is why these weaknesses are so problematic for any other performance goal.

Age and Gender and Advantage+ Audience

One of the primary complaints about Advantage+ Audience is that age maximum and gender aren’t audience controls. You can provide an age maximum and gender, but they are only audience suggestions.

Once again, this should not be a big deal if you can accurately define the action that you want, like a purchase. But it otherwise has the potential to make Advantage+ Audience unusable when using any other performance goal.

Earlier, I mentioned having this challenge with leads. It’s not always a problem, but I’ve found that when I begin to get “surprisingly good results,” it’s usually because a high percentage of my budget is getting spent on an older audience.

There’s unfortunately no easy way around it. I’ve tried an age maximum suggestion, but Meta immediately ignores it because I can get more of the results I “want” by reaching an older audience. You can switch to original audiences and define the age maximum, but that’s not necessarily a great solution either. I don’t necessarily want to cut off all ad spend to an older audience. I just don’t want it to monopolize my budget.

The Fatal Flaw

The fatal flaw in Meta ads targeting and optimization is that, except in rare cases, Meta doesn’t know what we want. We’ve defined what we want in very general terms (link clicks, landing page views, leads, ThruPlays, etc.).

It’s the combination of this weakness in optimization and the growing reliance on algorithmic targeting that makes the problem worse. Meta’s systems are powerfully good at finding people who are willing to perform the action that you want.

Unfortunately, the action that “you want” isn’t necessarily exactly what you’ve defined with the performance goal. And that’s what leads to low-quality results and wasted ad spend.

The Solution: It’s Complicated

To a point, it’s simple. We don’t necessarily need more targeting control. It shouldn’t be necessary to require the ability to restrict by age or gender. The solution also isn’t to eliminate Advantage+ Audience or audience expansion through the various Advantage Audience tools.

The solution hasn’t changed since I first complained about it years ago: We need to be able to more precisely define what we want.

Instead of any old traffic, we want people who are going to spend time on our website, perform several actions, and make return visits.

Instead of any views of our videos, we want people who signal interest (willingly watch without being forced, search out more videos, and provide other engagement).

Instead of any leads, we want people who perform other actions that prove that they are quality leads — even if it’s not an eventual purchase.

I’m not sure how exactly Meta would implement this. It could be by providing a secondary performance goal. Or maybe it would be providing options of “volume” and “quality” actions where other factors are considered.

But the current flaws in optimization are old and primitive. Not only were they unacceptable years ago, they enhance the problem with the development of algorithmic targeting.

This needs to be fixed.

Your Turn

What are your thoughts?

Let me know in the comments below!

The post Meta Ads Targeting and Optimization’s Fatal Flaw appeared first on Jon Loomer Digital.

Today’s targeting is a combination of advertiser inputs and Meta’s algorithmic distribution, with the aim to get you as many of your desired actions as possible within your budget. But advertisers have a common misunderstanding of how much control they actually have.

What I often hear from advertisers who want control is that they switch from Advantage+ Audience to original audiences because they don’t trust Meta’s algorithmic distribution. But more often than not, they’re dealing with algorithmic distribution there, too.

As someone who is focused on educating advertisers on how the systems work, it’s been an incredibly frustrating discussion. While it makes sense to me, it simply does not to most.

That’s why I wrote this post. And, more importantly, why I created the following grid.

Grid Comparison

Are your targeting inputs respected? Or they viewed as merely suggestions? Will your audience be expanded?

The grid above is a summary of how much your targeting inputs matter, depending on the setup. When you use Advantage+ Audience, your inputs are treated the same in all cases, regardless of the performance goal. But there are some contributing factors to how much your inputs matter when using original audiences.

An important point here is that we don’t know how much your audience suggestions matter, though my tests have indicated that they matter very little. We also don’t know how much your audience is expanded when expansion happens with original audiences, though my tests again suggest that it’s similar to when using Advantage+ Audience.

The problem here is that Meta provides little to no transparency on this matter. It’s entirely solvable, of course. I’ve long asked for a breakdown that would generate separate rows of results for our targeting inputs and those who were reached beyond them. Until that exists, we’re left guessing.

Still, we can approach this as if audience suggestions are as impactful to Advantage+ Audience as your targeting inputs that can be expanded when using original audiences. And when we do, we can provide a bit more clarity regarding what we can control and what we cannot.

Advantage+ Audience (Any Performance Goal)

Advantage+ Audience is largely algorithmically driven. That means that regardless of the performance goal, Meta will search out the people who are most likely to perform the action that you want. This freedom can help lower costs and improve results (not without some risk).

Respected Inputs:

Anything entered into Audience Controls within the ad set is a tight constraint that will be respected. Meta will not show ads to people outside of these controls.

When you make customizations here, the following are respected…

Location

I often hear complaints that location isn’t actually respected, but that’s a misunderstanding of how location is controlled from the beginning.

You will reach people who are either “living in or were recently in” your selected location. If a city, that will also include a radius of 10+ miles beyond it. You cannot isolate people who only live in a certain area.

Yes, location targeting is messy. But it doesn’t get messier as a result of using either Advantage+ Audience or original audiences. The same rules apply.

Minimum Age (18-25)

You can set a minimum age, but it can’t be any lower than 18 or higher than 25. How low you can go will depend upon the targeted country.

Note that age maximum is not an audience control option.

Excluded Custom Audiences

You can also exclude people who are within a certain custom audience. An example would be excluding those who bought the specific product that you are promoting.

As is the case with locations, this method is not perfect. Custom audiences are almost never complete for various reasons, and you’re most likely to notice this with exclusions. If you reach a current customer while excluding them with custom audiences, it’s not because of whether you are using Advantage+ Audience or original audiences. These exclusions are treated the same in either case.

Languages

This control is unlikely to be used all that often.

As it says in the tooltip, Meta recommends specifying languages only when they aren’t common to your selected locations.

Audience Suggestions:

You can provide audience suggestions with Advantage+ Audience, but it is purely optional.

Meta says they will “prioritize audiences matching this profile before searching more widely.” So, that means that nothing you provide here is a tight constraint.

That includes settings for:

• Custom Audiences
• Age Range
• Gender
• Detailed Targeting (interests and behaviors)

Note that there is an audience control for age minimum that is respected, but there is also an age range that is only a suggestion. In other words, the range here (minimum and maximum) will only be seen as a suggestion and your ads can be shown to people outside of it if Meta believes it will lead to more of the actions that you want.

The age minimum within audience controls will be respected. But it doesn’t necessarily need to be the same setting as what is in audience suggestions. If you do set an age minimum in audience controls, you won’t be able to set a suggested range below it.

For example, when setting the audience control age minimum at 25, you can’t set the suggested minimum range below 25.

A key takeaway here is that there are no audience controls for age maximum or gender.

Original Audiences (Conversions Performance Goal)

If you switch to original audiences while using the performance goal to optimize for conversions or value, algorithmic expansion will be significant. This is when distribution is likely to be most similar to what you get when using Advantage+ Audience.

Understand that this has nothing to do with your campaign objective. For example, you can use the Sales objective but select the performance goal to Maximize Impressions. The factor that impacts these differences is the performance goal.

Respected Inputs:

• Minimum Age
• Maximum Age
• Gender
• Location
• Custom Audience Exclusions
• Language

Audience Expanded:

• Lookalike Audiences
• Detailed Targeting

This is where I’ve found advertisers are most surprised. When optimizing for conversions or value and you provide a lookalike audience for targeting, Advantage Lookalike is automatically turned on and cannot be turned off.

The same is the case for detailed targeting. If you provide detailed targeting, Advantage Detailed Targeting is automatically turned on and cannot be turned off.

In theory, your audience will only be expanded if it will lead to more or better results. But all indications I’ve had is that your audience expands significantly in these cases.

It Depends:

You can provide custom audiences with original audiences, but whether your audience expands will depend upon whether you leave the box for Advantage Custom Audience checked. It will be checked by default.

If it’s unchecked, you can run remarketing ads that only target people in your selected custom audiences. If you check that box, you’ll reach people well beyond that group. Based on my tests, that expansion is similar to what happens when providing custom audiences as suggestions with Advantage+ Audience.

Original Audiences (Link Clicks/Landing Page Views)

Of course, what is expanded and what isn’t by default — and whether you can turn that expansion off — varies depending on your performance goal. If you select a performance goal to maximize link clicks or landing page views, things are slightly different.

Respected Inputs:

• Minimum Age
• Maximum Age
• Gender
• Location
• Custom Audience Exclusions
• Language

Audience Expanded:

Here, only Advantage Detailed Targeting is on by default without an option to turn it off.

This was a change that rolled out in early 2024.

It Depends:

When using original audiences, you will always have the option of turning Advantage Custom Audience off (assuming you remember to uncheck the box). When optimizing for link clicks or landing page views, you will also have the option of turning off Advantage Lookalike to focus on your selected lookalike audiences.

Original Audiences (Any Other Performance Goal)

For any other performance goal (Reach, Impressions, Post Engagement, ThruPlays, etc.), you’ll have slightly more control over whether your audience is expanded when using original audiences.

Respected Inputs:

• Minimum Age
• Maximum Age
• Gender
• Location
• Custom Audience Exclusions
• Language

Audience Expanded:

Nothing is expanded by default.

It Depends:

In this case, Advantage Detailed Targeting can be turned on if you so desire.

Advantage Custom Audience and Advantage Lookalike are both optional.

What Should You Do?

So now you should understand that algorithmic distribution beyond your targeting inputs is likely to happen regardless of your decision to use Advantage+ Audience or original audiences. There are times when original audiences do give you more control. But that added control isn’t always required, or even beneficial.

There isn’t a one-size-fits-all approach to this. But here is how I approach it…

1. When Using the Conversions Performance Goal and Purchase Conversion Event

Keep in mind that you can select conversion events other than Purchase. But when using Purchase as your goal conversion event, I recommend using Advantage+ Audience (if not Advantage+ Shopping). The algorithm will adjust in real-time to show your ads to people most likely to purchase. That flexibility should only help you.

Even if your clients are primarily women and you can’t set gender as an audience control, the algorithm should adjust when Purchase is your goal event. Meta doesn’t want to waste money on people who don’t lead to that action (this could be an issue for other types of optimization).

2. When Using the Conversions Performance Goal and Other Conversion Events

If you select a conversion event other than Purchase, I’d still recommend that you use Advantage+ Audience. However, you should monitor it closely to make sure that the algorithm doesn’t exploit weaknesses that may lead to low-quality results.

Once again, understand that the algorithm’s focus is getting you as many of the goal action that you want within your budget. That’s not an issue when the goal event is a purchase. You’re not in danger of getting low-quality purchases this way. But that could be an issue for leads or other actions.

But I emphasize the word “could.” Don’t assume it. I’ve actually seen it go both ways. I’ve used Advantage+ Audience to generate leads at a lower cost that are also at a high quality. And I’ve also seen the algorithm suddenly favor the highest age bracket, resulting in low-quality leads. And the issue, of course, is that we can’t set an audience control for age maximum.

3. When Using Any Other Performance Goal

This is a bit of a loaded hypothetical because I don’t recommend using other performance goals generally since there is always the potential for low-quality results. The reason is that the algorithm will always look to exploit weaknesses in placements or the user pool to get you as many of the action you want. That can be a big problem when optimizing for clicks or engagement.

The truth is that switching from Advantage+ Audience doesn’t solve this problem. But you can at least limit your audience pool by age maximum or gender, if that is important. And this is where it can be an issue if your business serves primarily women or a specific age group.

Why is it a problem? If you want post engagement or video views, Meta’s delivery algorithm only cares about getting you more post engagement or video views. It doesn’t care whether potential clients see your ads. If men click on your ads or watch your videos, Meta will take that as a signal that more men should see your ads.

Your Turn

How do you approach audience inputs and expansion?

Let me know in the comments below!

The post When Do Targeting Inputs Matter? appeared first on Jon Loomer Digital.

To suggest that my perspective on Meta ads targeting has changed during the past year is an understatement. It’s completely transformed. This evolution wasn’t immediate and was reinforced through a series of tests.

Understand that it wasn’t easy to get here. It’s reasonable to say that my prior advertising strategy could have been boiled down to targeting. It was the most important step. Great ad copy and creative couldn’t overcome bad targeting.

It’s not that I don’t care about reaching a relevant audience now. It’s that the levers we pull to get there are no longer the same.

I’m getting ahead of myself. This post will help explain how I got here. I’ve run a series of tests during the past year that have opened my eyes to just how much things have changed. They’ve helped me understand how I should change, too.

In this post, we’ll discuss the following tests:

• Test 1: How Much Do Audiences Expand?
• Test 2: How Much Remarketing Happens When Going Broad?
• Test 3: Do Audience Suggestions Matter When Using Advantage+ Audience?
• Test 4: Comparing Performance and Quality of Results
• Test 5: Understanding the Contribution of Randomness to Results

Let’s get to it…

Test 1: How Much Do Audiences Expand?

One of my primary complaints ever since Advantage Detailed Targeting (then Detailed Targeting Expansion) was introduced is the lack of transparency.

We know that Meta can expand your audience beyond the initial targeting inputs, but will this always happen? Will your audience expand a little or a lot? We have no idea. I’ve long asked for a breakdown that would solve this problem, but I don’t anticipate getting that feature anytime soon.

The same questions about how much your audience expands also apply to Advantage Lookalike and Advantage Custom Audience. It’s a mystery.

This is important because we can’t always avoid expansion. If your performance goal aims to maximize conversions, value, link clicks, or landing page views while using original audiences, Advantage Detailed Targeting is automatically on and it can’t be turned off.

The same is true for Advantage Lookalike when your performance goal maximizes conversions or value.

Are we able to clear up this mystery with a test?

The Test

I don’t believe that there’s any way to prove how much our audience is expanded when Advantage Detailed Targeting or Advantage Lookalike are applied. But, there is a way to test this with Advantage Custom Audience. While it won’t definitively prove how our audience is expanded with the other two methods, it could provide a roadmap.

This test is possible thanks to the availability of Audience Segments for all sales campaigns. Once you define your Audience Segments, you can run a breakdown of your results to view the distribution of ad spend and other metrics between three different groups:

• Engaged Audience
• Existing Customers
• New Audience

For the purpose of this test, this breakdown can help us understand how much our audience is expanded. All we need to do is create an ad set using original audiences where we explicitly target the same custom audiences that are used to define our Audience Segments.

So, I did just that, and I turned on Advantage Custom Audience.

I used the Sales objective so that the necessary breakdown would be available.

The Results

My only focus with this test was to uncover how my budget was distributed. Performance didn’t matter.

In this case, 26% of my budget was spent between my Engaged Audience and Existing Customers.

Since the custom audiences I used for targeting matched how I defined my Audience Segments, we can state definitively that, in this case, Meta spent 74% of my budget reaching people outside of my targeting inputs.

What I Learned

This was groundbreaking for my understanding of audience expansion. Up until this point, whether or not Meta expanded my audience — and by how much — was a mystery. This test lifted the curtain.

These results don’t mean that the 74/26 split would apply in all situations universally. Many factors likely contribute to the distribution that I saw here, not limited to…

• Performance goal
• Conversion event
• Budget
• Size of remarketing audiences

We also don’t know if a similar split happens when applying Advantage Detailed Targeting or Advantage Lookalike. While we don’t know, this at least gives us a point of reference rather than having to make a blind guess.

Read More

Check out the following post and video to learn more about this test:

How Much Do Audiences Expand Using Advantage Custom Audience?

Test 2: How Much Remarketing Happens When Going Broad?

Even before we had Advantage+ Shopping Campaigns and Advantage+ Audience, some advertisers swore by using original audiences to “go broad” (no inputs for custom audiences, lookalike audiences, or detailed targeting). While unique, this approach was largely based on gut feel, with limited ways to prove how ads were getting distributed. They could only provide results as evidence that it was effective.

The addition of Audience Segments to all sales campaigns would allow us to provide a bit more insight into what is happening when going broad.

The Test

I created a campaign with the following settings…

• Campaign Objective: Sales
• Performance Goal: Maximize Conversions
• Conversion Event: Complete Registrations
• Targeting: Original Audiences using only location and custom audience exclusions
• Placements: All

The Results

Recall that we already had a remarketing distribution benchmark with the prior test. In that case, we explicitly defined the custom audiences we wanted to reach within targeting. In this case, I didn’t provide any such inputs.

And yet…

Even though no inputs were provided, Meta spent 25% of my budget on reaching prior website visitors and people who were on my email list (both paid customers and not).

What I Learned

I found this to be absolutely fascinating. While we will struggle to get any insight into who the people are that Meta reached outside of remarketing, the fact that 25% of my budget was spent on website visitors and email subscribers is important. It shows that Meta is prioritizing showing my ads to people most likely to convert.

This realization helped improve my confidence in a hands-off approach. If the percentage were closer to 0, it may show disorder. It could suggest that the broad targeting approach is based in smoke and mirrors and your inputs are necessary to help steer the algorithm.

What was most shocking to me is that the remarketing distribution was nearly identical, whether I used Advantage Custom Audience and defined my target or went completely broad. This was a whole new realization.

While the first test helped me understand how much Meta expands my targeting inputs, the second made me question whether those inputs were necessary at all. I’d spend about the exact same amount reaching that desired group in each case.

Read More

Check out the following post and video to learn more about this test:

25 Percent of My Budget Was Spent on Remarketing While Going Broad

Test 3: Do Audience Suggestions Matter When Using Advantage+ Audience?

While you have the option to switch to original audiences, the default these days is Advantage+ Audience. Meta strongly encourages you to take this route, warning that switching to original audiences can lead to a drop in performance.

When using Advantage+ Audience, you leverage Meta’s AI-driven algorithmic targeting. You have the option to provide audience suggestions, but it’s not required.

Meta says that even if you don’t provide suggestions, they will prioritize things like conversion history, pixel data, and prior engagement with your ads.

But, is this true? And how pronounced is it?

The Test

We could test this by again leveraging a manual sales campaign with Audience Segments. I created two ad sets:

• Advantage+ Audience without suggestions
• Advantage+ Audience with suggestions that match my Audience Segments

Since I can use custom audiences that exactly match the custom audiences used to define my Audience Segments, we can get a better idea of just how much (if at all) these audience suggestions impact delivery.

A reasonable hypothesis would be that while Advantage+ Audience without suggestions will result in remarketing (potentially in the 25% range, as we discovered when going broad). But, it’s likely to make up a smaller percentage of ad spend than when providing suggestions that match my Audience Segments.

But, that didn’t play out…

The Results

Once again, quite shocking.

The ad set that used custom audiences that match those used to define my Audience Segments resulted in 32% of my budget spent on that group.

By itself, this seems meaningful. More is spent on remarketing in this case than when going broad or even using Advantage Custom Audience (wow!).

But, check out the results when not providing any suggestions at all…

Your eyes aren’t deceiving you. When I used Advantage+ Audience without suggestions, 35% of my budget was spent on remarketing.

What I Learned

Every test surprised me. This one shook me.

When I provided audience suggestions, I reached the people matching those suggestions less than when I didn’t provide any suggestions at all. Providing suggestions was not a benefit. It didn’t seem to impact what the algorithm chose to do. That same group was prioritized either way, with or without suggesting them.

It’s not clear if this would be the case for other types of suggestions (lookalike audiences, detailed targeting, age maximum, and gender). But, the results of this test imply that while audience suggestions can’t hurt, it’s debatable whether they do anything.

As is the case in every test, there are several factors that will contribute to my results. Budget and the size of my remarketing audience are certainly part of that. And it’s also quite possible that I won’t always see these same results if I were to run the test multiple times.

It remains eye-opening. Not only is Advantage+ Audience without suggestions so powerful that it will prioritize my remarketing audience, it’s possible that Meta doesn’t need any suggestions at all.

Read More

Check out the following post and video to learn more about this test:

Audience Suggestions May Not Always Be Necessary

Test 4: Comparing Performance and Quality of Results

I’ve encouraged advertisers to prioritize Advantage+ Audience for much of the past year. It’s not that it’s always better, but it should be your first option. Instead, it seems that many advertisers find every excuse to distrust it and switch to original audiences.

Advertisers tell me that they get better results with detailed targeting or lookalike audiences. And even if they could get more conversions from Advantage+ Audience, they’re lower quality.

Is this the case for me? I decided to test it…

The Test

I created an A/B test of three ad sets where everything was the same, beyond the targeting. Here are the settings…

• Objective: Sales
• Performance Goal: Maximize Conversions
• Conversion Event: Complete Registration
• Attribution Setting: 1-Day Click
• Placements: All

The three ad sets took three different approaches to targeting:

• Advantage+ Audience without suggestions
• Original audiences using detailed targeting (Advantage Detailed Targeting)
• Original audiences using lookalike audiences (Advantage Lookalike)

Since the performance goal is to maximize conversions, Advantage Detailed Targeting and Advantage Lookalike would automatically be applied for the respective ad set, and it could not be turned off. The audience is expanded regardless.

The ads were the same in all cases, promoting a beginner advertiser subscription.

The Results

In terms of pure conversions, Advantage+ Audience led to the most, besting Advantage Detailed Targeting by 5% and Advantage Lookalike by 25%.

Recall that this was an A/B test, and Meta had 61% confidence that Advantage+ Audience would win if the test were run again. Maybe as important, a less than 5% confidence that Advantage Lookalike would win.

But, one of the complaints about Advantage+ Audience relates to quality. Are these empty subscriptions run by bots and people who will die on my email list?

Well, I tracked that. I created a separate landing page for each ad that utilized a unique form. Once subscribed, these people received a unique tag so that I could keep track of which audience they were in. The easiest way to measure quality was to tag the people who clicked on a link in my emails after subscribing.

Once again, Advantage+ Audience generated the most quality subscribers.

Is this because Advantage+ Audience leaned heavily into remarketing? We can find out with a breakdown by Audience Segments!

Nope! More was actually spent on remarketing for the Advantage Detailed Targeting ad set. Advantage+ Audience actually generated the fewest conversions from remarketing (though it was close to Advantage Lookalike).

What I Learned

This test was different than the others because the focus was on results and quality of those results, rather than on how my ads were distributed. And, amazingly, Advantage+ Audience without suggestions was again the winner.

Of course, we’re not dealing with enormous sample sizes here ($2,250 total spent on this test). It’s possible that Advantage Detailed Targeting would overtake Advantage+ Audience in a separate test. But, what’s clear here is that the difference is negligible.

There just doesn’t appear to be a benefit to spending the time and effort required to switch to original audiences and provide detailed targeting or lookalike audiences. I’m getting just as good results (even better) letting the algorithm do it all for me.

As always, many factors contribute. I may get better results with Advantage+ Audience because I have extensive history on my ad account. But, as mentioned in the results section, it’s not as if it led to more results from remarketing.

The fact that Advantage+ Audience won here isn’t even necessarily the main takeaway. There could be some randomness baked into these results (more on that in a minute). But, this test further increased my confidence in letting the algorithm do it’s thing with Advantage+ Audience.

Read More

Check out the following post to learn more about this test:

Test Results: Advantage+ Audience vs. Detailed Targeting and Lookalikes

Test 5: Understanding the Contribution of Randomness to Results

There was something about that last test — and really all of these tests — that was nagging at me. Yes, Advantage+ Audience without suggestions kept coming out on top. But, I was quick to remind you that these tests aren’t perfect or universal. The results may be different if I were to run the tests again.

That got me thinking about randomness…

What percentage of our results are completely random? What I mean by that is that people aren’t robots. They aren’t 100% predictable when it comes to whether they will act on a certain ad. Many factors contribute to what they end up doing, and much of that is random.

If there’s a split test and the same person would be in all three audiences, which audience do they get picked for? How many of those random selections would have converted regardless of the ad set? How many converted because of the perfect conditions that day?

It might be crazy, but I felt like we could make an example of randomness with a test.

The Test

I created an A/B test of three ad sets. We don’t need to spend a whole lot of time talking about them because they were all identical. Everything in the ad sets was the same. They all promoted identical ads to generate registrations for my Beginners subscription.

I think it’s rather obvious that we wouldn’t get identical results between these three ad sets. But, how different would they be? And what might that say about the inferences we make from other tests?

The Results

Wow. Yes, there was a noticeable difference.

One ad set generated 25% more than the lowest performer. If that percentage sounds familiar, it’s because it was the exact same difference between the top and bottom performer in the last test. But in that case, that difference “felt” more meaningful.

In this case, we know there’s nothing meaningfully different about the ad sets that led to the variance in performance. And yet, Meta had a 59% confidence level (nearly the same as the level of confidence in the winner in the previous test) that the winning ad set would win if the test were run again.

What I Learned

Randomness is important! Yet, most advertisers completely discount it. They test every detail and make changes based on differences in performance that are even narrower than what we saw here.

Think about all of the things that advertisers test. They create multiple ad sets to test targeting. They try to isolate the best performing ad copy, creative, and combination of the two.

This test taught me that most of these tests are based in a flawed understanding of the results. Unless you can generate meaningful volume (usually because you’re spending a lot), it’s not worth your time.

Your “optimizing” may not be making any difference at all. You may be acting on differences that would flip if you tested again — or if you let the test run longer or spent more money.

It’s even reasonable to think that too much testing will hurt your results. You’re running competing campaigns and ad sets that drive up ad costs due to audience fragmentation and auction overlap — all for a perceived benefit that may not exist.

I’m not saying that you should never test anything to optimize your results. But be very aware of the contributions of randomness.

Read More

Check out the following post to learn more about this test:

Results: Identical Ad Sets, a Split Test, and Chaos

My Approach Now

You’re smart. If you’ve read this far, you can infer how these tests have altered my approach. My strategy is drastically simplified from it once was.

I lean heavily on Advantage+ Audience without suggestions, especially when optimizing for conversions. Of course, Advantage+ Audience isn’t perfect. If I need to add guardrails, I will switch to original audiences. But when I do, I typically go broad. I rarely ever use detailed targeting or lookalikes now.

I also rarely use remarketing now, which is insane considering it once made up the majority of my ad spend. Since remarketing is baked in, there are few reasons to create separate remarketing and prospecting ad sets now. Especially when I’d normally use general remarketing (all website visitors and email subscribers) because I felt these people would be most likely to convert.

This also means far fewer ad sets. Unless I’m running one of these tests, I almost always have a single ad set in a campaign.

It doesn’t mean I’m complacent in this approach. It means that the results of these tests have raised my confidence that no targeting inputs will not only perform just as well, but oftentimes better. And I know that there are exceptions and factors that contribute to my results.

Maybe things will change. But, I no longer feel the need to micromanage my targeting. Based on the results of these tests — and of my results generally — it’s no longer a priority or a factor that I worry about.

And that, my friends, is quite the evolution from where I was not long ago.

Run Your Own Tests

I’m always quick to point out that my results are at least partially unique to me. Whether you’re curious or skeptical, I encourage you to run your own tests.

But, do so with an open mind. Don’t run these tests hoping that your current approach will prevail. Spend enough to get meaningful results.

Maybe you’ll see something different. If you do, that’s fine! The main point is that we shouldn’t get stuck in our ways or force a strategy simply because it worked at one time and we want it to work now.

Replicate what I did. Then report back!

Your Turn

Have you run tests like these before? What results did you see?

Let me know in the comments below!

The post 5 Meta Ads Tests that Transformed My Perspective on Targeting appeared first on Jon Loomer Digital.

There are several AI-powered enhancements that are not currently part of the core Advantage+ Creative toolbox. You can opt-in to join a test of the new AI generation features.

My assumption is that the enhancements available within these tests will be a moving target. When new enhancements become available, they’ll likely be sent to testing first. As of the time of this post, there are four enhancements that are part of this test, and this has grown quickly during the past few weeks.

As of this moment, you may be able to test the following:

• Image expansion
• Background generation
• Text extraction optimization
• Expand video

Let’s discuss how you can join this test and how each enhancement appears to work…

Access the Tests

Go to your Advertising Settings.

Under “Creating Ads,” there’s a box for Advantage+ Creative. Click that.

You will then have an option to opt-in to “Test new enhancements.” Check the box.

I haven’t found any documentation on the process for opting into these tests, so the details we see here are important.

First, this…

You are eligible to test new enhancements if you are currently opted into all Advantage+ creative enhancements. These test enhancements will be tested across all eligible campaigns for this ad account.

There is plenty of room for interpretation here because it’s not entirely obvious to me what this means. It appears that these tests will only apply if you accept all Advantage+ Creative enhancements for a given ad.

And then this…

We may show fewer than 5% of your ad impressions with new enhancements. This can help us improve our creative enhancements and increase performance for your ads. Turning this off will not affect your Advantage+ creative preferences.

When these enhancements are tested, they “may” account for fewer than 5% of your ad impressions. I can only assume that Meta would have used “will” here if it would definitely be fewer than 5%. But, the main thing is that it won’t be many.

Once opted in, there’s a box below that will allow you to choose the specific tests that you want to allow.

As of this moment, I’ve enabled the four enhancements that are available to me. As you can see by the start dates, Meta is rolling these out quickly. Once I’ve opted in, I’m automatically opted in to any new enhancement (and you can individually opt out).

If you click Edit Tests, you can get more details about each individual enhancement.

Image Expansion

I can confirm that this enhancement was originally part of the core Advantage+ Creative toolbox. For whatever reason, it’s been moved to testing.

Maybe it has some bugs to iron out, but image expansion could be an enormously valuable enhancement. If you provide a square image, Meta could automatically expand it for 9 x 16 using AI.

This isn’t just a matter of zooming and cropping. Meta will generate the top and bottom, as the example shows above.

Background Generation

Along with image expansion, I believe this enhancement first became available about a year ago. However, my notes indicate it was initially only available for Catalog Ads.

Not all images are eligible for this enhancement. Although Meta doesn’t clarify, my assumption is that this would only work for images with a solid background. Meta will then use AI to generate options with different backgrounds.

Overlay text will also be added. While that could be from your headline, it’s also possible that text extraction (the next feature) could be the source of this text.

Text Extraction Optimization

Text extraction is a bit more mysterious. As you can see from the screenshot above, “keywords and phrases” can be taken from your original text and displayed in certain locations (overlays, footers, prominent headlines, and something called an info chip).

We don’t have any examples of this. Not sure how Meta determines these keywords and phrases. And, as stated in the screenshot above, you will not get a preview of how your ads will look with this enhancement.

One day, you might. But while this is a test, you’ll be flying blind.

Expand Video

Okay, we’re saving the best for last. Video expansion is pretty great.

The example that Meta provides is a good one. You upload a landscape video. Meta uses AI to generate the top and bottom so that you can have something suitable for 9 x 16.

In the example, the sky is merely an extension of the top of the video, but it looks good. The fact that moving water was generated on the bottom was more advanced — there is no indication that water is there in the original video.

Should You Turn These On?

You will need to be trusting, if not a bit adventurous, to turn this on. I’m turning all four enhancements on for my main ad account. If you have a sensitive client who might be upset if some of these aren’t perfect, you may want to turn it off.

But, that’s also mostly the case for any Advantage+ Creative enhancement. There’s some trust required to use them. You can turn off any of the main enhancements that you find problematic, but at that point these tests wouldn’t be eligible.

Personally, there’s a certain amount of “letting go” that I’ve had to do with Advantage+ Creative enhancements. Since there isn’t a breakdown, we aren’t able to see how our ads perform when a specific enhancement is used. But, when you consider all of the different enhancements that might be applied, the sample size for any single one will be negligible anyway.

I’ve mostly embraced these enhancements with the understanding that they aren’t always used. When they are, it’s because Meta thinks it will help me get better results.

If you’re a control freak, maybe don’t worry about this. One day, these features will move into your main Advantage+ Creative toolbox. You can make the call on each individual enhancement at that point.

Your Turn

Have you turned this on?

Let me know in the comments below!

The post Test New AI Generation Features in Ads Manager appeared first on Jon Loomer Digital.

Advertisers often complain about paying to reach people they believe should have been explicitly excluded using custom audiences. The assumption is that Meta has chosen to ignore exclusions. But, the effectiveness of these exclusions is mostly within our control.

We most often hear this related to existing customers. There are two primary scenarios where this comes into play:

1. Advantage+ Shopping using an Existing Customer Budget Cap.

Advantage+ Shopping Campaigns allow you to set a cap on how much you will spend on existing customers.

This approach relies on the definition of your Existing Customers audience segment within your Ad Account Settings.

2. Manual campaign with a custom audience exclusion.

You can also run a manual campaign and exclude your existing customers by listing out the custom audiences that reflect that group.

If you use Advantage+ Audience, that would be within the Audience Controls.

If using original audiences, you can exclude custom audiences.

But, even if you use these settings, you will probably still reach some of your custom audiences. Why?

Here are the three most likely reasons (along with a myth about audience expansion)…

1. Completeness and Accuracy of Data Provided

In order to exclude every existing customer, you must first completely and accurately define your customers with custom audiences so that Meta can do just that. But, this is far more difficult than it sounds, approaching unreasonable.

Here’s an example of how I’ve defined my existing customers…

It’s a mixture of data file custom audiences and website custom audiences. But, I guarantee it’s incomplete.

To troubleshoot, ask yourself these questions…

Do your excluded custom audiences actually include existing customers?

It may seem like a silly question, but one of the first mistakes that advertisers make in this area is that they mess up the parameters that define a group of people. Look no further than inflated conversion reporting happening because the Purchase event is firing for the wrong stage.

Do your excluded custom audiences exclude all customers or only some?

When creating a custom audience based on your email list, have you confirmed that you’ve included every customer for every product? All customers historically, or only a specified period of time?

I should also point out that, depending on how you interpret Meta’s Custom Audience Terms of Service, you may be required to remove customers who have opted out of your list. So, there may be paying customers who you can’t include in the custom audience.

This may be pointing out the obvious, but website custom audiences are capped at 180 days. If you exclude your existing customers using this approach and your business is more than six months old, the audience will be incomplete.

And of course, there’s a long list of potential issues with website custom audiences and completeness. The most obvious is iOS opt-outs. Meta specifically said that the result of opt-outs would be smaller custom audiences.

That will create holes in your exclusions.

2. Meta’s Ability to Match the Audience

This mostly applies to data file custom audiences, where you provided a customer list to create a custom audience. Just because you uploaded a customer list that includes a specific person doesn’t mean that Meta will be able to match that customer’s details to a Facebook profile.

If you only include a list of email addresses, they need to be matched to Facebook users who provided those same addresses in their profiles. Facebook profiles may be old and outdated. Maybe your customer used a business email address that isn’t associated with their profile.

The more columns of data you provide for first name, last name, email address, phone number, and physical address, the higher the match rate will be. But, you can guarantee you won’t get a 100% match rate.

It’s anecdotal, but advertisers tend to see anywhere from 20 to 70% match rates from customer lists. The ability to match is only as good as the completeness and accuracy of the data. But even then, it’s not guaranteed to match a Facebook profile that’s used for exclusions.

You could also make the argument to include website custom audiences here. If a user is blocking cookies, browsing incognito, or using other privacy settings that impact the data that can be sent back to Meta (not to mention iOS opt-outs), Meta’s ability to match and exclude users is impeded.

3. Meta’s Ability to Actually Exclude Them

This is more theory than reality, and it assumes that the source of the problem isn’t #1 or #2 above. Essentially, it would mean that despite accurately and thoroughly defining your existing customer custom audiences, you are still paying to reach the people you shouldn’t. Meta knows that a specific person falls within your exclusions, but you reach them anyway.

Maybe it’s due to a bug. Maybe it’s because Meta doesn’t care about your stinking exclusions.

I’m not saying that this is impossible. But, of the three possible explanations, it’s the least likely. It’s also very difficult, if not impossible, to prove.

By “least likely,” I don’t mean that bugs rarely happen or that Meta is always trustworthy. I mean that there are so many obvious reasons for holes in exclusions, we don’t really need to resort to conspiracy theories to explain them.

The Expansion Myth

I’ve seen the theory that audience expansion doesn’t respect your custom audience exclusions. Specifically, this is related to using original audiences when Advantage Detailed Targeting or Advantage Lookalike are turned on.

The way I understand it, the source of the theory is this passage in Meta’s documentation related to Advantage Detailed Targeting…

And a similar passage from Meta’s documentation related to Advantage Lookalike…

For Advantage Detailed Targeting, Meta says that you can still exclude “targeting selections outside of detailed targeting (such as age, gender, location and language).” For Advantage Lookalike, “you can add targeting selections as exclusions if you don’t want our system to consider certain demographics such as Locations, Age, Gender etc.” Meta didn’t mention custom audiences!

But, is this an intentional omission? In both cases, it’s clear that Meta isn’t providing an exhaustive list. “Such as” language when listing out what can be excluded from Advantage Detailed Targeting and an important “etc.” to wrap up exclusions for Advantage Lookalike could suggest, maybe, that custom audience exclusions aren’t respected.

I’m not buying this argument. You can still exclude custom audiences in either case. It’s far from definitive that the reason you can still reach some of these people is due to expansion.

According to this theory, the proof is that if you optimize for a top of funnel action that doesn’t require expansion, third-party reporting tools show that you reach fewer existing customers as a result. But, this is less a function of the incredibly low quality results you get from top of funnel optimization than any proof that the exclusion works in this case.

If you’re still not convinced, look no further than Advantage+ Audience. Audience Controls are where you set the specific parameters that Meta will respect. These are not suggestions, but tight constraints.

One of those controls is excluded custom audiences.

If you believe that your custom audience exclusions aren’t respected when using original audiences when expansion is on, then maybe you should use Advantage+ Audience instead. This seems backwards, though, since the entire benefit of Advantage+ Audience is that the algorithm has more freedom to reach people who are likely to convert than when using original audiences. It would be odd if it were Advantage+ Audience that would respect your exclusions while they may not be with original audiences.

But, again, I’m confident that the belief that exclusions aren’t respected with expanded audiences is a misinterpretation. When in doubt, go with the most likely explanation. And there are lots of them.

Your Turn

What are your feelings about the causes behind reaching excluded existing customers?

Let me know in the comments below!

The post 3 Holes in Existing Customers Exclusion for Meta Ads appeared first on Jon Loomer Digital.

In 2023, Meta made a big change to location targeting that had significant negative impact on some industries. An update may help, at least when creating advertising to reach travelers.

Originally, advertisers had several options when targeting people by location.

If you wanted to isolate only the people living in or traveling in a location, you could. But with the change a year ago, the only option was to reach people “living in or recently in” a location.

If you only wanted to reach locals, you couldn’t. If you wanted to avoid locals and only focus on people traveling, you couldn’t. Unless the algorithm is incredibly smart, wasted ad spend is inevitable.

While there isn’t a fix for targeting locals, the latest update could be a big improvement for those in the tourism industry.

The Change

When you select a city (city of New York) or region (state of New York), you may see a checkbox (not every ad account has it as I write this). This is a critical element. If you do not select a city or region (for example, you only select countries), you will not see this option.

As far as I can tell, this option is available regardless of the objective and performance goal. It also doesn’t seem to matter whether you use Advantage+ Audience or original audiences. The only slight variation is that the objective appears to influence whether the box is checked by default (you can uncheck it).

Here’s what it says:

To improve performance, we’ll show ads to people interested in your selected cities and regions, for example people showing intent to travel to these locations or make purchases there. This only includes people in the same country as each location you select.

When you check that box, Meta will expand your audience based on the following:

• Recently visiting or living in that city or region
• Searching for terms and Marketplace listings related to that city or region
• Interacting with ads or Pages related to that city or region
• Having friends living in that city or region
• Living in towns or cities close to that city or region

Meta ran an experiment that suggests turning this on can lead to a 6.7% lower cost per result. Here are details of that experiment:

This result is based on an experiment run between March 11, 2024 and March 18, 2024. The experiment found that using location targeting to reach people most likely to respond led to a median cost per optimized event that was 6.7% lower than only reaching people living in or recently in a city or region.

I would love to see experiments for advertising that would benefit most from this. For example, what was the impact on results for businesses within the tourism and hospitality industries? Instead, I assume these are generic results that combine verticals.

An Example

Let’s assume that you run ads for a hotel in New York City. You could select only the city of New York and 25 miles around it, but that will only include people living or recently there. If they’re traveling, they likely already have their hotel booked. You could target the entire United States, but that’s surely to lead to waste.

Instead, you can select New York City and turn this option on. Pulling from the list above, you can then also reach people who…

• Searched for terms and Marketplace listings related to New York City
• Interacted with ads or Pages related to New York City
• Have friends living in New York City

The first two are most likely to be helpful in this case. It’s not clear how much recency matters when it comes to searching for terms or interacting with ads. But, it would be logical to assume that Meta will put more value on the most recent interactions.

The friend connection could also use clarification. The likelihood that someone has friends in or near a big city is high. A logical assumption is that Meta will place greater value on friendships where there is more interaction. For example, if you have a Facebook friend in the promoted city, but you haven’t interacted with them for 10 years, there’s no reason to show that person ads.

Other Benefits

Meta lists the following verticals that may benefit most from location expansion:

• Travel: Reach people who may be looking for accommodation or activities
• Entertainment: Reach people who are searching for shows, concerts and activities
• Retail: Reach people who are looking to travel to a location that is close to physical stores
• Professional services: Reach people looking to travel to your location who may be interested in your products or services
• Restaurants: Reach people looking to travel who may want to book meals and restaurant reservations

A key point to remember here is that the location will only be expanded to include people within the country you’ve selected. While people may technically search to travel outside of their country, this expansion will not pick up those people.

Should You Use This?

If you are in any of the verticals listed above, the answer is rather obvious: Yes, you should probably turn this on and take advantage of it.

Knowing advertisers well, my guess is that most others will either turn it off or be upset if they unknowingly leave it on. But, I have doubts that leaving this on will hurt your results.

This feature is all about taking advantage of opportunities if they’re there. It doesn’t mean that a huge chunk of your budget will shift to people outside of the area you targeted. It could be a handful of people or no one at all. This simply gives Meta the ability to reach those people if it will help you.

Meta specifically mentions that you may want to turn this off when promoting businesses “in sensitive verticals (eg, healthcare, pharmaceuticals, biotech),” but this will likely be the exception.

Again, this won’t even come up for advertisers who target by country since you’ll need to select a city or region for targeting. If this does apply to you, my recommendation is to test it extensively. Do not assume that it’s bad. Allow performance to guide you.

It Remains Imperfect

It’s easy to focus on the limitations on this update, so let’s address those…

1. You still can’t isolate only travelers. There’s no way to avoid spending money on people who live in the same city or region as your business.

2. No solution for international travel. While this is great for larger countries like the US where travel within the country is common, it doesn’t help small destination countries. In those cases, tourism is predominantly from outside of the country.

3. You still can’t isolate locals. I know that this update has nothing to do with it, but there is a clear need to bring back the ability to restrict targeting to local residents. Think schools, politics, daycare, and certain services (lawn care, plumbing, roofing) that would only be useful to locals.

It would be nice. Meta surely knows about these pain points. Advertisers have been screaming about them for over a year now.

Your Turn

Will this update help you?

Let me know in the comments below!

The post Location Expansion: Meta Advertising to Reach Travelers appeared first on Jon Loomer Digital.

We should always test our assumptions. We may think that something works, or maybe it worked at one time, but it’s important to verify that it remains the path forward.

Testing our targeting strategies was the focus of a recent blog post, and I ran a test of my own as an example. This post will highlight the setup and results of the test.

I tested using the following three targeting strategies:

1. Advantage+ Audience without suggestions
2. Detailed Targeting with Advantage Detailed Targeting
3. Lookalike Audiences with Advantage Lookalike

It’s important to understand that the results of this test are not universal. I will address some of the potential contributing factors at the end of this post.

Here’s what we’ll cover:

• Campaign Basics
• Targeting
• A/B Test Setup
• Surface Level Data
• Conversion Results
• Quality
• Remarketing and Prospecting Distribution
• Potential Contributing Factors
• What it Means

My goal isn’t to convince you that your approach is right or wrong. My hope is that my test inspires you to run a similar one of your own so that you can validate or invalidate your assumptions.

Let’s begin…

Campaign Basics

I created a campaign using the Sales objective.

Within that campaign, I created three ad sets. Each used the following settings…

1. Performance Goal: Maximize conversions with Complete Registration conversion event.

My goal is to get registrations on a lead magnet. The reason I’m using the Sales objective is to get access to Audience Segments data (I’ll address that later).

2. Attribution Setting: 1-day click.

I recommend using a 1-day click attribution setting for most non-purchase events.

3. Budget: $25/day per ad set ($750 per ad set overall)

The total spent on the test was about $2,250.

4. Locations: United States, Canada, and Australia.

I would normally include the United Kingdom, but it is no longer allowed for split testing.

5. Placements: Advantage+ Placements.

6. Ads: 1 static and one using Flexible Ad Format. The Flexible version utilized four different images.

Each ad sent people to a different landing page with a unique form. All three landing pages and forms appear identical to the user. This was done so that I could confirm results in my CRM — not just the number of registrations using each form, but what these people did once they subscribed.

Targeting

Each ad set utilized a different targeting approach.

1. Advantage+ Audience without suggestions.

There isn’t much to show here. This allows the algorithm to do whatever it wants.

2. Detailed Targeting with Advantage Detailed Targeting.

I used Original Audiences and selected the following detailed targeting options:

• Digital Marketing Strategist
• Advertising agency (marketing)
• Jon Loomer Digital (website)
• Digital marketing (marketing)
• Online advertising (marketing)
• Social media marketing (marketing)

Because I’m optimizing for conversions, Advantage Detailed Targeting is automatically turned on. I cannot prevent the audience from expanding.

3. Lookalike Audiences with Advantage Lookalike.

I selected lookalike audiences based on the following sources:

• Customer List
• Power Hitters Club – Elite (Active Member)
• All Purchases – JonLoomer.com – 180 Days

Because I’m optimizing for conversions, Advantage Lookalike is automatically turned on and can’t be turned off.

A/B Test Setup

I ran an A/B test of these three ad sets in Experiments. The key metric for finding a winner was Cost Per Result. That “result” was a registration.

I ran the test for 30 days and chose not to have it end early if Meta found a winner.

I’m glad I did it this way because Meta’s confidence in the winner wasn’t particularly high and it changed the projected winner a couple of times. This allowed the test to play out until the end.

Surface Level Data

Before we get to the results, I found this interesting. Beyond testing how these three would perform, I was curious if the cost for delivery would be much different. This, of course, could have an impact on overall performance.

The difference in CPM is minor, but it could be impactful. It was $.68 cheaper to deliver ads using Advantage+ Audience than Lookalikes. The difference in CPM between Advantage+ Audience and Detailed Targeting was $.89.

While this may not seem like much (it’s not), that resulted in the delivery of between 1,500 and 2,000 more impressions when using Advantage+ Audience. It doesn’t mean that a lower CPM will lead to more results, but we should bookmark this metric for later.

Conversion Results

According to Ads Manager, Advantage+ Audience led to 9 more registrations than Detailed Targeting and 36 more than Lookalikes.

The overall costs for these results weren’t great, but that’s also consistent with what I’ve seen when running split tests. Because these tests prevent overlap, delivery will be less efficient. Of course, “good results” weren’t the goal here.

The difference between Advantage+ Audience and Detailed Targeting may not be statistically significant, but the difference between the two and Lookalikes certainly was. The A/B test results support this assumption.

It’s possible that if the test were run again, Detailed Targeting would come out ahead (Meta estimates a 36% chance of that happening). But, it’s very unlikely (under 5%) that Lookalikes would come out on top.

Recall that each ad sent people to a different landing page that utilized a different form. This way, registrants were given a unique tag so that I knew which audience they were in. These landing pages and forms were only used for the test.

Keep in mind that the results in Ads Manager reflect all registrations, and this can include registrations for other lead magnets. This could happen if someone who subscribes to the lead magnet I’m promoting then subscribes to another (I email about other lead magnets in my nurture sequence).

The numbers from my CRM aren’t much different, but they are different.

The disparity is greater when looking at the “true” results. Advantage+ Audience led to 14 more registrations than Detailed Targeting and 43 more than Lookalikes.

At least some of this difference might be related to the slight difference in CPMs. But, keep in mind that Lookalikes had the second lowest CPM of the three targeting strategies, but it performed the worst.

Quality

One of the first arguments I hear from advertisers when it comes to leveraging Advantage+ Audience over old school targeting approaches is that it’s more likely to lead to low-quality results. Was that the case here?

I was prepared to measure this. It’s one of the reasons that I used unique forms for each ad set. It allowed me to get a deeper understanding of whether these registrants did anything else.

I’d consider my funnel atypical when it comes to most businesses who collect registrations. I don’t have an expectation that many of them will buy from me within 30 days. I look at it as more of a long-tail impact, and many of the people who buy from me do so years later.

Because of that, we can’t make any reasonable assessment of registration quality based on sales at this stage. While two purchases came in via Advantage+ Audience and two from Detailed Targeting so far, these are hardly statistically significant. And it could change dramatically in a matter of months or years (and I don’t want to wait until then to publish this post).

But, there is another way to assess quality, and I first applied this when comparing lead quality from instant forms vs. website forms. Have these registrants performed a funnel event by clicking specific links in my emails?

Once again, the count of “quality clicks” is incomplete, but we can make some initial evaluations. Here’s where we stand at this moment…

While Advantage+ Audience led to a higher volume of registrations, it was not at the expense of quality. It generated 17% more quality registrants than Detailed Targeting and 54% more than Lookalikes.

These numbers are imperfect and incomplete since, like I said, a true evaluation of whether or not the registrations were “quality” can’t be made for quite some time. But, it at least shows the difference in engagement. If someone hasn’t engaged with my emails, they are less likely to be an eventual customer.

Remarketing and Prospecting Distribution

I promised I’d get back to this when I explained using the Sales objective at the top. I could have used the Leads objective (or even Engagement), but I chose Sales for one reason: Access to data using Audience Segments.

When running a Sales campaign (Advantage+ Shopping or manual), some advertisers have access to Audience Segments for reporting.

Once you define your Engaged Audience and Existing Customers, you can use breakdowns to see how your budget and results are distributed between remarketing (Engaged Audience and Existing Customers) and prospecting (New Audience).

This is something that isn’t necessarily incredibly meaningful, but I find it interesting. It gives us an idea of how Meta finds the people who are likely to perform our goal event. I used this as the primary way to compare distribution using four different targeting approaches in another test.

Within that test, I saw remarketing take up 25 to 35% of my budget, regardless of the targeting approach. In that case, I ran each ad set concurrently and didn’t run an A/B test. This test could be different since it’s a true A/B test.

Here are the breakdowns…

It’s a lot of numbers, but the distribution between remarketing and prospecting is very similar in all three cases.

• Advantage+ Audience: 9.2% remarketing, 90.8% prospecting
• Detailed Targeting: 10.1% remarketing, 89.9% prospecting
• Lookalikes: 8.7% remarketing, 91.3% prospecting

More remarketing happened with Detailed Targeting, though I wouldn’t consider that statistically significant. The type of remarketing was a bit more significant, however. Advantage+ Audience spent $10 on existing customers, whereas the other two approaches spent around $5 or under. Not a lot, obviously.

Maybe somewhat surprising is that more remarketing registrations came from using Detailed Targeting (25 vs. 16 for Lookalikes and 14 for Advantage+ Audience). While that creates a seemingly significant percentage difference, we’re also dealing with very small sample sizes now that may be impacted by randomness.

My primary takeaway is that distribution to remarketing and prospecting is about the same for all three approaches. My theory regarding why it’s so much less than when I ran my other three tests is that an A/B test splits a finite (and comparatively smaller) remarketing audience into three. There isn’t as much remarketing to go around.

Potential Contributing Factors

It’s important to understand that my results are unique. They are impacted by factors that are unique to my situation and you may see different results.

1. The Detailed Targeting selected.

Some advertisers swear by detailed targeting. Maybe they have certain options that are much more precise and make using them an advantage. Maybe I would have seen different results had I used a different selection of interests and behaviors.

These things are all true. But, you should also remember that no matter what our selections, the audience is expanded when optimizing for conversions. This is why I have my doubts regarding the impact of using specific detailed targeting options.

2. The Lookalike Audiences selected.

The lookalike audiences that I selected are based on sources that are important to my business. They include both prior registrants and paying customers. But, this was also my worst performing ad set. Maybe different lookalike audiences would have changed things.

Once again, I’m not wholly convinced of this because of the fact that lookalike audiences are expanded when optimizing for conversions. I have doubts regarding whether any of my lookalike audiences are that different that the algorithm wouldn’t eventually find itself showing my ads to the same people once expanded.

But, I can’t ignore the possibility. I was surprised that lookalikes performed so much worse than the other two, and the ones I selected could have contributed to those results.

3. Activity and history on my account.

This one is based primarily on theory because Meta isn’t particularly clear about it. We know that if audience suggestions aren’t provided when using Advantage+ Audience, Meta will prioritize conversion history, pixel data, and prior engagement with your ads.

It’s possible that I’m at an advantage because I have extensive history on my account. My website drives more than 100,000 visitors per month. There is a history of about a decade of pixel data.

Yes, this is possible. We just don’t know that for sure. Many advertisers jump into a new account and automatically assume that Advantage+ Audience won’t be effective without that history. Test it before making that assumption.

4. Industry.

It’s entirely possible that how each of these three approaches performs will differ based on the industry. Maybe some industries have detailed targeting that clearly makes a difference. That doesn’t seem to be the case for me, even though there are detailed targeting options that clearly fit my potential customer.

And… once again, we can’t ignore that your detailed targeting inputs will be expanded when optimizing for conversions.

5. Location.

Some of the responses I’ve received from advertisers regarding the viability of Advantage+ Audience refer specifically to their location. They say that Advantage+ Audience does not work where they are. Maybe that’s the case. I can’t say for sure.

6. Randomness.

One of the biggest mistakes that advertisers make is that they fail to account for randomness. Especially when results are close, do not ignore the potential impact of random distribution. The more data we have, the less it becomes a factor.

One of the tests on my list is to compare the results of three ad sets with identical targeting. What will happen? I’m not sure. But, a piece of me is hoping for chaos.

What it Means

As I said at the top, my goal with this test wasn’t to prove anything universally. My primary goal was to validate or invalidate my assumptions. I’ve been using Advantage+ Audience for a while now. I haven’t used detailed targeting or lookalikes for quite some time. But, these results validate that my approach is working for me.

Another goal for publishing these results is to inspire advertisers to create similar tests. Whether you use Advantage+ Audience, detailed targeting, lookalike audiences, or something else, validate or invalidate your assumptions.

A far too common response that I get from advertisers about why they don’t use Advantage+ Audience is something along the lines of, “This will never work for me because…” It’s based on an assumption.

That assumption could be because of an inability to restrict gender and age with Advantage+ Audience. But, as I’ve discussed, you should test that assumption as well — especially when optimizing for purchases.

Bottom line: These results mean that Advantage+ Audience without suggestions can be just as effective as, if not more effective than, detailed targeting and lookalikes. If that’s the case, you can save a lot of time and energy worrying about your targeting.

Test this yourself and report back.

Your Turn

Have you run a similar A/B test of targeting strategies? What did you learn?

Let me know in the comments below!

The post Test Results: Advantage+ Audience vs. Detailed Targeting and Lookalikes appeared first on Jon Loomer Digital.

I’ve been a Facebook-then-Meta advertiser since close to the beginning. This site exists (for 13 years strong now) because of my passion and deep understanding of how everything works. It’s been my pleasure sharing tips over the years to help keep you ahead of the curve.

That’s why the current path of Meta ads targeting pains me. My only goal is to help you understand where things are now and where they are heading so that you are best prepared. I’ve published several videos and posts to help explain what’s happening with targeting. The most common response I’m receiving is disbelief, if not outright defiance.

I am not trying to convince you that Advantage+ Audience is always effective or that you should go targeting-free with Advantage+ Shopping Campaigns. I want you to understand that your targeting inputs matter less than they ever did before. Knowledge of this is power because it helps advertisers better understand their role and where they can be most impactful.

Some of the things I’ve said and will repeat here aren’t up for debate. It’s how things work now. Too many advertisers simply don’t have a full understanding of how targeting works in the current environment. They are tweaking things and turning dials that have little or no connection to results.

But, the defensiveness runs deep, and I understand this. If you believe that the value you add as an advertiser is found, partially or entirely, within your targeting strategy, you will hate everything that I’m saying on the topic. It’s an attack on your way of life, and that’s scary.

This post may not fix that. It took me longer than I care to admit to accept it, and I was surely angry and defensive at first. But, I hope that this at least sends you in the direction of understanding.

Interests, Behaviors, and Detailed Targeting

First, Interests and Behaviors is the same category of targeting as Detailed Targeting. I include them all here because advertisers often misunderstand what Detailed Targeting means and lump it in with remarketing, lookalike audiences, and demographic adjustments.

This is the oldest method of targeting. It was a big deal when advertisers were given the ability to target people based on their interests and behaviors. It allowed us to isolate people based on specific interests that were related to what we were promoting.

It allows me, for example, to target people who may be interested in online-advertising content and products.

This was powerful since it would give me confidence that my ads were being shown to people who cared about, and were more likely to respond favorably to, my ad.

But, the current environment is not the same as that of 2014. The value of these inputs is not the same.

1. Inaccuracies.

I encourage you to take the time to go through the interests and behaviors that can be used to target you. Some of it is accurate. Some of it is outdated. And some of it is straight-up random.

I was originally going to list out all of the most random ways that advertisers can waste their money targeting me, but I honestly don’t know where to start. There are a lot of them. I wrote about this four years ago.

North Carolina State University ran a study in 2022 that estimated 30% of interests and behaviors used for targeting are inaccurate or irrelevant. These categories are far from perfect. We should treat them accordingly.

We assume that when we use detailed targeting that our ads will reach people who have an interest or experience directly related to that thing, but it’s not that simple. Meta seems to make inferences from random engagements that are far less meaningful.

2. Expansion.

This is a big one. It’s not new. But, advertisers continue to act surprised by or completely oblivious to this.

If you optimize for conversions, link clicks, or landing page views and you provide detailed targeting inputs, Advantage Detailed Targeting is automatically turned on. It can’t be turned off.

This means that your ads will reach people beyond those interests and behaviors if it can improve results. Your audience is expanded.

We don’t know how much your audience is expanded. We don’t know how much of your budget will be spent on the interests you listed and on people beyond those groups. But, this uncertainty matters.

There’s a very wide range of possibilities here. Maybe only a small percentage of your budget is spent on reaching people beyond your intended interests. Maybe most was spent on people you didn’t plan to target.

You should have concerns regarding the accuracy of detailed targeting inputs. You should also assume that there’s a distinct possibility that the results you get have more to do with the expansion of your audience than the inputs you provided.

While we can’t say definitively that interest targeting doesn’t matter at all, the amount of positive impact they can make is certainly in question.

Bottom line: My point isn’t that you can’t get good results while using detailed targeting. A common response I get from advertisers is that they get good results when they use interests. The point is that it’s questionable how much your selections of interests and behaviors impacted your results.

Lookalike Audiences

Like interest targeting, lookalike audiences are not new. When they were announced, lookalikes presented an enhancement from using interests only. Instead of guessing about what your customer was interested in, you could have Meta find people who were most similar to your customers.

While they made sense at one time, it’s questionable whether they remain relevant today. At the very least, they’re certainly less useful than they once were.

1. Expansion.

Once again, there’s a bit of fuzziness about the parameters you’re providing. When optimizing for conversions, Advantage Lookalike is automatically turned on and it can’t be turned off.

This means that you may reach people beyond the percentage of lookalike that you selected. We won’t know how much this is expanded or how much of your budget is spent on this expansion versus your selected audience.

2. Algorithmic Targeting.

I generally find it curious that advertisers will favor lookalike audiences over Advantage+ Audience (which we’ll cover in more detail shortly). Lookalike audiences are algorithmically driven. Meta will search for people similar to those in your source audience and compile an audience that is much, much larger.

Instead of using a lookalike audience based on your current customers, let’s instead assume you use Advantage+ Audience without suggestions. By definition, Meta will use signals like pixel activity, conversion data, and prior engagement with your ads to determine who should be in your audience.

It seems odd to be okay with Meta’s development of lookalike audiences but not with algorithmic targeting. There are very obvious similarities between the two.

How much impact do the lookalike audiences that you provide have on your results? Due to expansion, we don’t know. And why should we prefer it over Meta’s more recent algorithmic targeting developments?

Targeting Inputs are Deprioritized

You may not like it, but it’s clear what Meta is doing. If you use original audiences and optimize for conversions, your detailed targeting and lookalike audiences will be expanded. Those inputs are less important than they once were.

Of course, Meta doesn’t want you to use those approaches anyway. Meta wants you to use Advantage+ Audience.

While you can provide targeting inputs, it’s pretty darn obvious that Meta doesn’t think this is necessary. Otherwise, those inputs would be immediately available.

If you provide custom audiences, lookalike audiences, detailed targeting, age maximum, or gender, they will be used as audience suggestions.

This is the default way to impact targeting. While the option to provide targeting inputs using original audiences still exists, Meta works hard to discourage you. When you click to use original audiences, you’ll get an alert asking if you’re sure.

Meta’s tests show that you can improve your results by up to 33% if you use Advantage+ Audience over original audiences. It’s in Meta’s best interests that you get those superior results.

When it comes down to it, Meta may not even prefer that you use Advantage+ Audience. When creating a sales campaign, you are defaulted to Advantage+ Shopping Campaigns.

You still have the option of creating a manual sales campaign, but Meta clearly wants you to go this route.

Advantage+ Shopping Campaigns take algorithmic targeting even further. Your targeting inputs are virtually non-existent.

It’s not that you will always get better results using Advantage+ Audience or Advantage+ Shopping Campaigns. But, Meta has found that advertisers do get better results with these methods, on average. And your impact on targeting in either case is minimal.

Remarketing

I still remember how excited I was when advertisers were given the ability to target website visitors. It changed the entire industry.

You don’t need to convince me of the value of reaching people who are deeply connected to us. I lived primarily off of remarketing for a very long time. The question is whether much of the remarketing that we once did is still necessary.

Audience Segments for sales campaigns opened my eyes to this possibility. Once you define your Engaged Audience and Existing Customers (essentially your remarketing audiences), you can see how much of your budget is spent on remarketing while not even trying.

In my tests, it doesn’t matter whether I use Advantage+ Audience (with or without suggestions) or original audiences. I regularly see a similar distribution between remarketing and prospecting.

If Meta is going to prioritize your remarketing audience anyway, why is it necessary to create separate ad sets to reach your remarketing audience — especially a general remarketing audience (all website visitors, for example)?

The primary argument for remarketing now is if you have a unique message for a very specific group of people that would only be relevant to them. Minus such a message, it just doesn’t feel necessary.

Exceptions and Caveats

I’ve been careful to specify that the situations when detailed targeting and lookalike audiences are least impactful are when those audiences are expanded. The end result is likely more like Advantage+ Audience than you think.

But, there are times when you can turn expansion off — and it may even be recommended. If your performance goal is post engagement, ThruPlay, or just about anything other than a conversion (or link clicks and landing page views for detailed targeting), Advantage Detailed Targeting and Advantage Lookalike are options that can be turned on or off.

I’m not suggesting that turning off expansion will give you better results. Instead, your inputs obviously mean more if targeting is restricted to what you provide.

There are also times when using original audiences instead of Advantage+ Audience may be preferred, especially when optimizing for top-of-the-funnel actions. Not only do you get more control over detailed targeting and lookalike audiences, but age maximums and gender become tight constraints. If you’ve seen that your budget is wasted outside of your demographic preferences when using Advantage+ Audience, this is always an option.

That said, this still doesn’t have anything to do with your detailed targeting and lookalike audience selections.

How Much Does It Matter?

If I’m successful at nothing else with this post, I hope that you at least walk away with a new skepticism about your impact on targeting.

I said it before, but it requires repeating: This isn’t about whether Advantage+ Audience is superior to using interests and lookalikes. It’s that any difference between the three approaches has the potential of being completely random.

If you’re getting great results using a certain group of interests, it may be partially due to the interests you’re using. It may be mostly due to the expanded audience. We don’t know. The main thing is that the inputs you provided aren’t likely to be the main or only reason you’re getting those results.

Results from test after test are showing me this. Surface level metrics are nearly the same. Distribution between remarketing and prospecting are nearly the same. Results are nearly the same.

And when there’s a wider difference, it’s a disparity that often can’t be replicated when I recreate the test. It was random.

That’s why I want you to obsess less over these things. It’s not that I demand you stop using original audiences with interests and lookalikes. I just want you to stop obsessing over them. It’s unlikely that you found the perfect combination of targeting inputs.

Advertisers are superstitious creatures. Even if we know that something we’re doing isn’t why we’re getting great results, we don’t want to rock the boat. And that’s perfectly fine.

But, I encourage you to resist the need to over test your targeting. If you continue to create multiple ad sets for different groups of people, hoping to isolate the best performing selection of targeting inputs, you are likely doing more harm than good.

It’s also a potentially colossal waste of time that could be better spent on things that matter, like your ad copy, creative, landing page, and attribution.

The Direction We’re Heading

This should be obvious…

1. In a very limited number of situations, you can avoid having your detailed targeting and lookalike audiences expanded. In those that remain, they may be expanded by default, but you can turn it off. Meta wants you to turn it on.

2. When optimizing for conversions (and sometimes link clicks or landing page views), your ads can be delivered to people outside of the interests and lookalikes that you provide.

3. The default approach to targeting is Advantage+ Audience. Meta doesn’t want you to use original audiences and tries to discourage you from using them.

4. Meta doesn’t even seem to care if you provide any targeting at all with Advantage+ Audience. When you do, it’s merely a suggestion.

5. If you’re creating a sales campaign, it defaults to Advantage+ Shopping, which allows for virtually no targeting inputs at all. This is what Meta wants you to do.

Your targeting inputs matter far less than they ever did before. More importantly, Meta doesn’t seem to want or even need them. And the trend line is towards eliminating them entirely.

You can be upset about this, but I simply ask that you acknowledge it. Repeat after me:

“My targeting inputs mean less than ever before. Meta doesn’t want or need my targeting inputs. One day, I will likely lose all ability to control these things.”

Once you accept it, you can prepare.

How to Impact Who Sees Your Ads

This may seem like you’re placed in a helpless situation, but you’re not. Your targeting inputs may not matter much, but you can still impact who sees your ads.

1. Performance Goal. Think about it. This might be the most impactful control of all. Whether your audience is expanded or you’re using Advantage+ Audience, the algorithm is driven by finding people who will perform the action that you want, as defined by the performance goal. This includes the conversion event that you choose when optimizing for conversions.

What you define as your goal will drastically alter who sees your ad. Meta’s focus will be on helping get you that action.

2. Ad Copy, Creative, and Offer. A common claim is that the ad does the targeting now, and I don’t know that this is literally true. I haven’t seen Meta specify that the algorithm scans your copy for keywords to determine who sees your ad. But, it’s mostly semantics.

Your initial audience is likely determined by pixel activity, conversion data, and prior engagement with your ads. After that, it learns from who performs the action that you want. So, you want your ad copy, creative, and offer to attract your ideal audience.

You don’t want to attract a general audience. You want to attract very specific people. In a sense, you want your ad to repel people who aren’t your ideal customer.

These aren’t small things. Crafting effective copy, creative, and offers isn’t easy to do. Don’t feel as though a light-touch approach to targeting is somehow the easy way out. You still have work to do.

Your Turn

What’s your approach to reaching your ideal audience? Has it evolved?

Let me know in the comments below!

The post Meta Ads Targeting and an Advertiser’s Role, Explained appeared first on Jon Loomer Digital.

Are you still running Meta ads strategies that you used years ago? Do you ignore Meta’s best practices and recommendations because you swear that they don’t work?

My view of ad strategies isn’t absolute. There isn’t one approach that will always work for everybody in all situations. If you’ve found what works for you, great. Even if it’s inconsistent with what works most often, there are exceptions.

But, you also shouldn’t do this blindly. Don’t be stubborn about it. Don’t take an approach based on gut feel, a lack of trust in automation, or because something did or didn’t work a few years ago.

If you’ve been taking the same approach for the past year or longer, it’s important that you test your assumptions about what works and what doesn’t. And when you do, make sure it’s a scientific test that will provide meaningful results.

Running these tests can only be productive. It could reinforce what you believed to be true. Or the results may make you question whether what you’re doing is actually effective. You may see an alternative approach in a new light.

My advertising approach has changed dramatically over the years. I did not immediately embrace an evolving set of best practices. I was stubborn. But, my own tests have helped me understand that I was wrong. They also helped improve my confidence in another approach.

In this post, we’ll cover a handful of old school advertising targeting strategies and how you should test them against a more modern approach. Once you’ve tested, you can decide whether your stubbornness was right all along.

Testing Basics

Before we get to the old school strategies, it’s important to provide a framework for testing.

1. Use A/B Test.

I prefer to create A/B Tests in Experiments. Create the campaigns or ad sets that you want to compare first. Then go to Experiments and click to create an A/B Test.

Select the campaigns or ad sets that you want to compare. I ask you to test ad sets in two of the three examples below. In the third, you’d compare campaigns.

2. Focus on a Single Variable.

Everything about the two campaigns or ad sets should be identical except for a single variable. Since this post is about testing targeting strategies, everything beyond targeting should be the same. Make sure that there aren’t any other variables like placements or ad copy and creative that could result in differences in performance.

3. Your Key Metric

The Key Metric is what determines which campaign or ad set “wins” in an A/B test.

Make sure that this metric isn’t frivolous. What ultimately determines which ad set was better? If your goal is sales, then the key metric should be Cost Per Purchase. Do not use secondary metrics like CTR or CPC.

If your key metric is Cost Per Lead, you may want to take steps to measure the quality of those leads. Make sure that you send these leads to different forms so that you can keep track of them in your CRM.

4. Strive for meaningful results.

Your goal isn’t to find a winner quickly, it’s to find convincing results that actually mean something. Make sure that the budget dedicated to each competing campaign or ad set, combined with the length of the test, are enough to produce the volume that you need.

The longest you can run a test is a month. This would be my preference for a test that will help define your strategy going forward. Do not end the test early if a winner is found.

If the results become more convincing with time, that’s a good thing.

1. Interests and Lookalikes

There was a time when the ability to target people by interest, behavior, or lookalike audience was revolutionary. It gave advertisers targeting control and your ads were more likely to reach a relevant audience.

That isn’t always the case now. If you use Advantage+ Audience, any inputs you provide for detailed targeting or lookalike audiences will be suggestions.

This is why many advertisers have resorted to using original audiences. Targeting inputs in that case are more than suggestions — or we assume.

But, the reality is that even when using original audiences, your targeting inputs are rarely tight constraints. If you’re optimizing for conversions, link clicks, or landing page views, Advantage Detailed Targeting is automatically on.

If you optimize for conversions, Advantage Lookalike is automatically on.

In other words, we have no idea how much your selection of those interests and lookalike audiences actually matter. And based on my tests, they matter very little — if at all.

It’s not even clear that your audience suggestions matter when using Advantage+ Audience. They may actually be a detriment. This is why I recommend testing your current strategy with interests and lookalike audiences versus Advantage+ Audience without any suggestions at all.

Compare:

• Version 1: Original Audiences using Detailed Targeting or Lookalike Audiences
• Version 2: Advantage+ Audience without Suggestions

Key Metric: Cost Per Conversion (whichever event is most relevant)

Are you actually better off using original audiences to target interests or lookalikes? Maybe. But, prove it.

2. Gender and Age Control

One of the complaints I’ve heard from advertisers about Advantage+ Audience is the lack of control over age and gender.

You are only able to provide an age minimum within Audience Controls when using Advantage+ Audience.

Any age maximum or gender inputs you provide are audience suggestions. If Meta can get you more or better results by delivering your ads outside of those ranges, it will.

As a result, advertisers who feel these inputs are critical have favored original audiences. In that case, age and gender are tight constraints that will be respected.

Let’s assume that your customer is predominantly women aged 25-49. If Advantage+ Audience works the way that it should, whether or not ads are delivered to men or people outside of those age ranges will depend upon whether you can get your optimized actions from those other groups.

I’ve seen examples where businesses that serve women used Advantage+ Audience and 99% of the budget was spent on reaching women — even though gender is only a suggestion.

The key, though, is that you should optimize for conversions for this to be effective — preferably purchases. If reaching people who fall outside of expected gender and age range won’t lead to conversions, you’ll likely spend very little there.

Can you trust Advantage+ Audience without these controls? It’s worth testing for any type of conversion, especially purchases. Leads can be problematic since it’s possible you may get cheaper and lower quality leads this way — but, it’s worth testing. Engagement optimization is likely to go off the rails using Advantage+ Audience without those controls, but top-of-the-funnel optimization is problematic at its core.

Compare:

• Version 1: Original Audiences with Age and Gender Restrictions
• Version 2: Advantage+ Audience with Age and Gender Suggestions (if at all)

Key Metric: Cost Per Conversion (whichever event is most relevant)

Is it critical that you only reach people within your preferred demographic? Is it possible that Advantage+ Audience will waste money by reaching people outside of those groups? Maybe. But, prove it.

3. Remarketing

Look, my whole thing years ago was remarketing. I was generating a high volume of daily organic traffic, and ads allowed me to leverage this with highly relevant targeting.

But, things have changed. You can still target remarketing audiences. Those groups of people are surely just as relevant as they were years ago. What changed is the cost.

Targeting small groups of people is much more expensive than targeting large groups. Even though your website visitors may be three times more likely to convert, it may cost three (or five or 10) times more to reach them.

The other development is that Meta’s ad delivery algorithm has improved. Even if you use Advantage+ Audience without suggestions or go broad with original audiences, the algorithm will almost always prioritize a percentage of your budget to remarketing. We now know this due to Audience Segments.

When running Advantage+ Shopping Campaigns (or any Sales campaigns, if you have the update), you can breakdown your results by Audience Segments. I’ve often seen that between 25 and 35% of my budget is spent on people who have engaged with me (visited my website or subscribed to my email list) or bought from me.

Many advertisers continue to create campaigns with separate ad sets for prospecting and remarketing. But, since these two things happen at once without us even realizing it, is it still necessary?

For this test, we’ll need to compare campaigns since the old school approach is to use two ad sets. I would also use an attribution setting that is click only to prevent the remarketing ad set from inflating results with view-through conversions.

Also make sure that the combined budget of each campaign is the same. In other words, Version 2 using Advantage+ Audience should be the same as the sum of the two ad sets in Version 1.

Compare:

• Version 1: Campaign with Remarketing and Prospecting Ad Sets
• Version 2: Campaign with one Ad Set using Advantage+ Audience

Key Metric: Cost Per Conversion (whichever event is most relevant)

In addition to comparing the Cost Per Conversion, use your Breakdown by Audience Segments to see how your spend and results from remarketing compare.

Test Your Assumptions

I want you to test these because what I’ve seen from my own tests is quite clear. I’ve seen that…

1. Detailed targeting and lookalike audiences are rarely beneficial. Advantage+ Audience almost always gives me the same or better results.

2. Gender and age restrictions are rarely necessary. Especially when optimizing for purchases, the algorithm figures it out.

3. Remarketing is not the advantage it once was. It’s expensive to run stand-alone remarketing ad sets. Remarketing and prospecting happen together in the most optimal way now.

There are always exceptions, and I’ve even mentioned some of those cases in this post. But, if you are still utilizing some of these old school targeting strategies, I encourage you to run these tests yourself and allow for the possibility that more modern approaches may be more beneficial.

Your Turn

These are the types of tests that I often run to challenge my own assumptions. Once you’ve run these tests, I’d love to see your results.

Let me know in the comments below!

The post How to Test Meta Advertising Targeting Strategies appeared first on Jon Loomer Digital.

Instant forms allow advertisers to collect lead information via lead ads without sending people to an external website. In this post, we’ll cover every step of the instant form creation process.

To create your own instant form, there are a couple of requirements.

1. Use the Leads campaign objective.

2. Select a conversion location in the ad set that includes instant forms.

Then when creating your ad, go to the Destination section and click the button to create a new form.

The instant form creation process is separated into the following sections…

Note that the Review Screen step will only appear when using the Higher Intent form type.

Now let’s explain what goes into each step of the instant form creation process…

1. Form Type

If you’ve created instant forms before, Meta may pre-fill the form using information sourced from your Facebook Page, previous lead forms, and similar advertisers.

This is just a starting point, and you can edit any of the auto-generated suggestions.

First, name your form.

If you skip this step, a name will be generated for you. You’ll want to be sure to name it something to reflect what people are subscribing for because you will run into this later on.

There are three form types. “More Volume” will be selected by default.

• More Volume: Quick to fill out and submit
• Higher Intent: Add a review step to confirm sending info to improve lead quality
• Rich Creative: Opportunities to provide much more information about your business

The differences found when using Rich Creative can be found in the Intro step.

2. Intro

You have the option of providing a background image for your form. By default, you’ll use the image from your ad when this is turned on.

The option to upload a separate 1200×628 image is only available if you turn on the Greeting.

Provide a headline and description to explain why the person should provide their contact info. You can use either paragraph…

…or a list.

2. Intro (Rich Creative)

If you selected the Rich Creative form type, the Intro section is completely different.

Add a square 600 x 600 image to the top of this section.

Provide a headline (up to 60 characters).

Provide an overview (up to 80 characters). This is similar to the Description using the other form types, but it’s much shorter and only in paragraph format.

Benefits work more like the list version of the description with the other form types. With this optional section, you can provide up to three benefits (up to 57 characters).

The Rich Creative form type gives you the option of providing up to four sections that help build your story.

The How it Works section can also be labeled Get Started, More About Us, How We’re Different, and Highlights.

Regardless of what you label it, you can add two to five steps to this section that include a title and description. It’s completely customizable.

The Products section can also be labeled Services, Best Sellers, Plans, Courses, or Programs.

Regardless of how it’s labeled, this section is constructed with two to five carousel cards that feature a 1200 x 803 image, title, description, and two to three benefits.

The Social Proof section can feature Reviews, Accreditations, Certifications, and News Stories.

You can build this section with two to five carousel cards using a 1200 x 803 image, name, and quote (how this is labeled will depend on what you are featuring).

The optional Incentive section allows you to highlight a benefit to motivate people to provide their contact info. This section includes the incentive (up to 30 characters), description (up to 40 characters), and disclaimer (up to 40 characters).

What you provide here is completely customizable. Check out this blog post for more examples of how Rich Creative (formerly Custom) looks and works.

3. Questions

This section is broken up into two groups:

1. Custom questions
2. Contact information

In most cases, you may only ask for contact information. But the custom questions may be your best tool for managing lead quality.

Meta may recommend a few questions based on those that have been asked in the past.

Otherwise, you can create a question from scratch.

Multiple Choice allows you to craft a question with restricted options of potential answers.

Short Answer allows you to ask a question that yields an open ended, but brief, answer.

Conditional allows you to create a set of questions with conditional answers that change based on how someone answered a previous question.

This is accomplished with a CSV file. Here’s an example of what that might look like…

Appointment Request allows you to give people the ability to request a date and time to meet with you.

Slider allows you to ask questions that people can answer based on a predefined range. For example, they could rate on a scale of 1 to 10 how interested they are in buying a new car.

Advertisers can make any of these custom questions, other than Conditional, optional. When checked, people can skip the question.

You can make these custom questions even more impactful by turning on Conditional Logic (Note: You can’t make questions optional when this is on).

When turned on, a Logic column will be added to the answers.

“Go to a question” allows you to send a person who answers this way to a specific question — or create a new question that they’ll be asked.

“Submit Form” allows you to send a person who answers a specific way to the End page — or craft a new End page for these people.

“Close Form” allows you to send people who either don’t answer or provide an answer that indicates they aren’t a lead to a special end page. Their contact information will not be submitted.

The Contact Information portion of this section allows you to collect the basic information that you’ll need to reach out to a new lead.

The Description is optional and can be used to explain what you’ll do with the lead’s contact information. An example is “We’ll use your information to send you our weekly newsletters.”

The typical information you might request are email address, first name, and last name. Much of this information will be prefilled from a person’s Facebook profile.

Click Add Category for additional questions you can ask related to contact info.

Contact Fields…

User information…

Demographic questions…

Work information…

And national ID number…

Note that you may be restricted from asking for some of this information if you are promoting something that falls within a Special Ad Category.

4. Privacy Policy

Meta requires that you provide a link to your privacy policy when collecting contact information. Provide the link and optional link text.

If you don’t provide link text, the Privacy Policy link text will read “View [Page Name]’s Privacy Policy.”

You can also add custom notices like legal disclaimers to the default Facebook privacy disclaimer.

You’ll likely only use this when you feel you are legally required.

5. Review Screen

There isn’t anything to do here. The Review Screen is only relevant if you selected the Higher Intent form type.

If you did, the potential lead will see this final review before submitting the form…

6. Ending

We’re almost done!

If you didn’t use Conditional Logic when crafting custom questions, this will be a simple page. This will be what people see when they’ve completed your form.

It starts with a headline and description. It could be as simple as a “thank you” and that more information is coming via email.

There are four different action items that you can feature:

• Go to website
• View file
• Call business
• Redeem promo code

“Go to website” may be most common. You may simply send people to your website generally or an archive page.

“View file” allows your lead to download a PDF, PNG, or JPG file. You’ll need to upload it to Meta during this step.

“Call business” allows you to provide your phone number so that when leads complete your form on mobile, they can click a Call button to initiate a phone call.

And finally, “Redeem promo code” is a way to offer a promo code to reward your new lead, whether it was in exchange for contact information or as a pleasant surprise.

If you used conditional logic with custom questions, you’ll have two separate Ending pages: One for leads and one for non-leads (and potentially more, depending on how you structured your logic).

Messages for non-leads could be as simple as thanking them for their interest and directing them to your website.

Settings

Don’t miss the Settings button at the top right when creating your form.

There are three settings: Form Configuration, Field Names, and Tracking Parameters.

Within Form Configuration, the first thing you can do is define the language people will see in your form. This can help Meta with delivery. It will likely be your main language by default, and you may never need to change it.

The Sharing section is one I’ve always found interesting.

By default, it’s “Restricted.” This means that only people you reach with your ads can complete the form. But, that means that there is no viral potential. If someone shares your ad, their friends of leads can’t complete it.

There may be times when this is necessary. But, I prefer to keep this set at “Open” to allow for more completions. It’s really easy to miss.

You can change how the field names appear in your exports within the Field Names section. Note that this will rarely be necessary.

And finally, you can include tracking parameters to help identify where leads come from. This is info you’ll be able to see when you access leads via API, Download, or configured CRM.

Your Turn

Facebook lead ads were introduced in 2015, and they’ve evolved a whole lot over the years. What was once a very simple process has expanded in complexity. The result is a very long blog post to explain instant forms! To learn more about Facebook Lead Ads, make sure to check out my guide.

Do you use instant forms?

Let me know in the comments below!

The post A Guide to Instant Forms appeared first on Jon Loomer Digital.

There was a time when asking the question in today’s title would have been considered ridiculous. But, we can no longer ignore the trends. As much as we may want to fight it, targeting doesn’t matter nearly as much as it once did.

The way I phrased that was a soft landing. It left some wiggle room. Maybe it still matters, but not as much as before, right? But, let’s take it further.

It’s possible that targeting no longer matters at all.

Whoa, don’t come at me like that! I know. There are so many advertisers who still use the same strategy they’ve used for years. They insist it still works — and that it’s necessary. I know because I hear from them often.

I was one of those advertisers. If you were to go back far enough on this website, you’d begin to find quotes from me like this:

There are many factors that lead to success or failure of your Facebook ad campaign. But spoiler alert: Nothing is more important than targeting.

Or this:

Facebook ad targeting is one of the primary reasons why ads fail or succeed. You could have the perfectly crafted ad, but you shouldn’t expect it to work if it’s targeting the wrong people.

Things have changed. Our inputs mean less due to the move towards audience expansion and algorithmic targeting. In most cases, you can provide audience suggestions or inputs, but it’s questionable how much those inputs impact delivery.

And now that we have audience segments for sales campaigns, we can start to get more visibility into whether what we change matters at all.

Through my tests during the past month using four different ad strategies, it’s pretty clear: The strategy I chose did not seem to make any noticeable difference.

Allow me to explain…

Targeting Before

My quotes in the section above came from 2017, and I stand by them as being applicable at that point in time. Our targeting inputs absolutely did matter.

We defined the precise pool of people who should see our ads based on location, age, gender, custom audiences, lookalike audiences, and detailed targeting. Meta’s ad delivery optimization would then show ads to people within that pool who were most likely to convert.

If that initial targeting pool was flawed, we would not get results. Our inputs were important.

They were so important that Meta’s algorithm couldn’t fix broken targeting for us. It didn’t look at our inputs as suggestions. It didn’t prioritize our inputs initially before expanding to help us get better results.

We defined who could see our ads, and performance relied heavily on it.

Targeting Now

Of course, that’s no longer the case. The introduction of features like Advantage audience expansion and Advantage+ Audience means that we have various levels of control when it comes to who sees our ads:

• Things we definitively control
• Things we sorta control
• Things that have inconclusive impact and may not matter at all

The point of this article isn’t to say that today’s algorithmic targeting is better — or even that the control of the past was superior. Rather that it is what it is, and it’s possible that we’re paying far too much attention to factors we have little control over.

As we discuss control, I am going to focus only on cases when we’re optimizing for conversions. Otherwise, the factors that contribute to control will vary.

But, truthfully, if you’re able to optimize for conversions (and have conversion data available via the pixel or Conversions API), conversion optimization should be your priority. Top-of-funnel optimization is largely flawed, whether you control the audience or not.

What We Definitively Control

For each of these sections, we should differentiate between whether we’re using Advantage+ Audience or Original Audiences.

Advantage+ Audience: Factors We Control

• Minimum Age
• Languages
• Excluded Custom Audiences

These are within your Audience Controls. Meta will not serve ads to people under your set minimum age, within excluded custom audiences, or who don’t speak your selected language.

You may assume that location should fall here, too, but I omitted it intentionally. We’ll get to it.

Original Audiences: Factors We Control

• Minimum and Maximum Age
• Gender
• Languages
• Excluded Custom Audiences
• Custom Audiences (if Advantage Custom Audience is turned off)

There’s a bit more control here, but it’s minimal. When using Original Audiences, you can set a tight control on age range (both minimum and maximum) as well as gender. When using Advantage+ Audience, gender and custom audiences are suggestions (we’ll get to that). But when using Original Audiences, they are tight constraints.

What We Sorta Control

There’s one item that we omitted from above that we sorta control, and this applies to both Advantage+ Audience and Original Audiences: Location.

Way back in 2023, Meta changed our control over location targeting. Originally, we had four options:

• People living in or recently in a location
• People living in a location
• People recently in a location
• People traveling in a location

But, now it’s only “living in or recently in.” That means that you can’t isolate locals or travelers. This is why location is something we only sorta control.

No, Meta will not deliver your ads to people who don’t either live in or were recently in your selected location. You have control over that.

But, that doesn’t mean you have full control. If you want to only reach locals or travelers, you can’t. And that’s been a major frustration for advertisers.

What We Do That Has Inconclusive Impact

There’s a growing list of targeting inputs that we provide that may not matter at all. Or maybe they do. But, it’s not entirely clear whether they matter a lot, very little, or somewhere in between.

Advantage+ Audience: Inconclusive Impact

• Custom audiences
• Lookalike audiences
• Age maximum
• Gender
• Detailed targeting

All of these things are audience suggestions. It is entirely unclear whether they matter. Maybe they help give the algorithm initial direction. Maybe these suggestions are completely inconsequential.

Ultimately, your ads will be delivered to people who are likely to perform the action that you defined with your performance goal.

Original Audiences: Inconclusive Impact

• Custom audiences (if Advantage Custom Audience is turned on)
• Lookalike audiences
• Detailed targeting

When optimizing for conversions, Advantage Lookalike and Advantage Detailed Targeting are on by default and can’t be turned off. This means that your audience will be expanded and ads can be shown to people beyond those audiences.

In the case of custom audiences, you have the option of turning on Advantage Custom Audience.

Does that mean that if you get great results from your targeting inputs, expansion won’t happen? Does it mean that expansion always happens? Or does it mean that your inputs are no more than suggestions, like with Advantage+ Audience — this is simply a softer repackaging?

We don’t know. But, it’s entirely possible that inputs for audiences that can be expanded have minimal impact on delivery.

Here’s why I think that…

Look At This! (Targeting Test)

The image above is a summary of a test that I ran recently. It’s a sales campaign with four separate ad sets using a different targeting strategy:

1. Advantage+ Audience without suggestions
2. Advantage+ Audience with suggestions
3. Original Audiences using custom audiences with Advantage Custom Audience turned on
4. Original Audiences with no targeting inputs beyond country (going broad)

This test wasn’t about comparing performance (Cost Per Conversion) because too many factors impact that. But, if you’re curious, those results were almost exactly the same.

I was more concerned about whether my ads were delivered differently. I used audience segments to get an idea of how much of my budget was spent reaching my engaged audience and existing customers (in other words: Remarketing).

The difference was negligible and could be due to randomness, rather than the specific strategy.

Without getting too in the weeds of that test, my inputs or targeting strategy didn’t seem to have any impact on the distribution of my budget between remarketing and prospecting. At the very least, there’s strong evidence that at least 25% of my budget will go to remarketing, no matter what my approach.

The question we can’t answer is whether my strategy or targeting inputs impacted the prospecting audience. Since results are essentially the same, it would be logical to assume the difference is minimal. But, there’s no way to say for sure.

Does Remarketing Matter?

There was a time when remarketing made up a very large percentage of my advertising efforts. But, that’s no longer the case. More accurately, I no longer create ad sets that isolate custom audiences.

In the section about targeting we definitively control, custom audiences is listed under Original Audiences (assuming you turned Advantage Custom Audience off). You can still run remarketing campaigns. But, the question is whether you should.

As you can see in my pie charts above, between 25 and 35% of my budget was spent on remarketing using all four strategies. This includes using Advantage+ Audience without suggestions and Original Audiences while going broad.

I should also mention that it’s possible, if not extremely likely, that even more than that is spent on remarketing. Audience segments for engaged audience and existing customers do not include engagement custom audiences. So, we don’t know how much of my budget is spent on people who engaged with my ads, but didn’t click to my website, make a purchase, or join my email list.

While I don’t explicitly run remarketing campaigns, I’m still remarketing. And that’s kind of the beauty of how Meta is distributing my budget. Prospecting and remarketing happens all within a single ad set.

What This Could Mean

If what I’ve found in this limited test scales and isn’t a random blip, it should make you think about how you run ads.

It may not matter whether you use suggestions with Advantage+ Audience.

It may not matter whether you use Advantage+ Audience or Original Audiences and go broad.

It may not matter if you use Original Audiences with one of the targeting options that expands your inputs.

It’s quite possible that in all cases, Meta’s ad delivery algorithm will dedicate a similar percentage of your budget to remarketing and the rest to prospecting.

When I discovered this possibility, it was freeing. When you realize that none of your inputs make that much of a difference, you stop obsessing over how you do it. It allows you to focus more of your time on ad copy and creative.

But, just as importantly, you realize that all of those separate ad sets to segment your targeting were probably completely unnecessary. Because each ad set, assuming the audience was impacted by expansion, likely reached a very similar group of people. You’re better off consolidating your budget.

My takeaway is that Advantage+ Audience without suggestions is likely sufficient for me. And there’s no reason to run multiple ad sets in one campaign at the same time for the purpose of segmenting targeting groups.

The main exception to this could be if you need to tightly control the ads that are shown to individual audience segments, but that should not be the norm for most advertisers. And ultimately, you could hurt your performance by forcing such control.

So… Does Targeting Still Matter?

I don’t have a definitive answer for you. There’s still too much we do not know about the impact of our inputs and how our ads are delivered.

At the very least, our targeting inputs certainly mean far less than they did before. Remarketing isn’t necessary, in many cases. It’s possible that you only need to use Advantage+ Audience without suggestions now, assuming you’re optimizing for conversions.

I’ve seen enough to decide that these inputs are no longer impactful enough (if at all) to be all that concerned about them. Because it seems that no matter what approach I take, my ads get delivered in a similar manner.

Summary Grid

I put together a grid to summarize the level of audience control advertisers have over targeting, broken down by approach. I’ve been told that people like summary grids. So, here you go…

Your Turn

What’s your feeling about targeting these days? Does it still matter?

Let me know in the comments below!

The post Does Targeting Still Matter? appeared first on Jon Loomer Digital.

Meta is rolling out a uniquely useful update to ads attribution that will allow you to isolate the first conversion after an ad view or click.

In this post, I’ll walk you through the following:

1. Where to find it
2. Meta’s definitions
3. What it plainly means
4. How you can apply it

Let’s begin…

Where to Find It

Access the Columns dropdown menu within Ads Manager (the menu to the left of Breakdown).

At the bottom, select “Compare Attribution Settings.”

If you aren’t already using this feature, it’s time to start. It’s enormously valuable for providing context to reported conversions.

If you have this update, the Compare Attribution Settings menu should look like this…

This feature allows you to generate columns for each attribution setting. That way, you can see how your reported conversions are distributed across the various view and click attribution windows.

Once you select any of those attribution settings, you’ll get some new options.

The default view is “All Conversions.” But you now have the option of viewing “First Conversion” or “Both.”

Meta’s Definitions

Let’s go through Meta’s literal definitions here.

All Conversions: See every conversion that happened after an ad view or click.

First Conversion: See only the first conversion that happened after an ad view or click.

If you select “First Conversion” or “Both,” you’ll see some additional info…

First conversion counts only the initial measurable conversion that happens after someone viewed or clicked on your ad, which is why results will be lower than for all conversions. First conversion metrics are unavailable for date ranges before July 15, 2023.

The linked Meta resource says the following:

To see every measurable conversion that happened after an ad click or view, choose All conversions. To see only the first measurable conversion that happened after an ad click or view, choose First conversion.

What it Plainly Means

This definition is confusing if taken literally. Let’s consider an example.

After clicking your ad, a person performs the following conversion events in order during a seven-day period…

1. View Content
2. Custom Event (1-Minute View)
3. Add to Cart
4. View Content
5. Custom Event (1-Minute View)
6. Add to Cart
7. Initiate Checkout
8. Purchase
9. View Content
10. Add to Cart
11. Initiate Checkout
12. Purchase

You could interpret Meta’s definition to mean that only the initial View Content conversion is counted because it was the first conversion. That’s luckily not the case.

Instead, only the first instance of an individual conversion event within the attribution window will be counted. For our example, here’s how All Conversions might be reported…

• View Content: 3
• Custom Event (1-Minute View): 2
• Add to Cart: 3
• Initiate Checkout: 2
• Purchase: 2

If you used First Conversion instead, it would be reported like this…

• View Content: 1
• Custom Event (1-Minute View): 1
• Add to Cart: 1
• Initiate Checkout: 1
• Purchase: 1

How this impacts your results will depend quite a bit on the business. The types of conversions most likely to be impacted are those that happen multiple times. Several independent Purchase events may be much more common for an ecommerce business than for one selling training or services.

You’re likely to see the biggest disparities between engagement-type conversion events. That includes things like View Content, Add to Cart, and Initiate Checkout since a transaction is never completed. It also includes custom events (if you’ve created them) for things like time spent and scroll depth.

This is certainly true for me. Take a look at this difference in reported 15-second views using First Conversion and All Conversions…

I see very little difference in reported registrations or purchases. When I do, I have a good idea why that happens.

One example of purchase behavior on my website is that someone will first sign up for my PHC – Elite membership so that they can get a discount on a one-on-one session. So, they’ll complete two separate purchase events.

How You Can Apply It

My advice is to approach this as a way to add necessary context to reporting. Do not look at First Conversion as a replacement for All Conversions. Just like you shouldn’t look at 1-day click as a replacement for the default 7-day click and 1-day view attribution. This gives you more data so that you can better understand what your results mean.

When it comes to purchases, I would not discard the “All Conversions” view. If one person made five separate purchases within your attribution window, their initial engagement with your ad contributed to all five purchases. Ignoring the other four would be foolish.

By adding the First Conversion view, you get some helpful context. Instead of five customers, you have one. But, that one customer bought a lot of stuff!

As suggested earlier, I expect this is going to be most helpful for times when Ads Manager can very easily inflate your numbers. This is especially the case with custom events.

Even if you limit attribution to 1-day click, engagement-based custom events will be inflated. If you send someone to a video on your website, and they watch 20 videos, that would result in 20 custom event fires for each of those videos (assuming you created them like I did). This kind of behavior makes these results unusable.

But if you can isolate by only the first view, we suddenly have information we can work with. We now have a much better idea of the number of people who executed all of those events.

A Note on Value

On one hand, Meta could have named this a “Unique” metric, which is mostly what this does. We’ll find out the number of people (or Accounts Center Accounts) that performed these actions. But, counting only the first one will be relevant for value-related metrics.

Meta will only count the first purchase after engaging with your ad. That means that only the value of that first purchase will count towards your ROAS and Purchase Value metrics.

You will need to find what works for you, but I’d certainly recommend using All Conversions when measuring your advertising’s ROAS. As always, consider the various Attribution Settings (valuing click over view data) when evaluating those results.

Your Turn

How will you use this feature?

Let me know in the comments below!

The post First Conversion vs. All Conversions for Meta Ads Attribution appeared first on Jon Loomer Digital.

A long-running mystery in the era of algorithmic Meta ad delivery can finally be answered: How much do our targeting inputs matter?

I’ve run a test that reveals how much Meta distributes ad delivery between my remarketing audiences and prospecting while relying on algorithmic targeting and expansion. The results are surprising, encouraging, and enlightening.

This post is a bit of a rabbit hole, but it’s worth it. Let’s get to it…

Background and Historical Context

Years ago, targeting was simple. We made a series of selections using custom audiences, lookalike audiences, detailed targeting, and demographics. We then expected that our ads would reach people within those groups.

But, that all began to change with the introduction of Advantage audience expansion. At first, it was an option. Then expansion became the default for detailed targeting and lookalike audiences with certain objectives. And finally, Meta introduced the next level of hands-off, algorithmic delivery: Advantage+ Shopping Campaigns and Advantage+ Audience.

Luckily, Meta made audience segments available to provide important visibility into how Advantage+ Shopping Campaigns were delivered. We could then see how much of our budget went to our engaged audience, existing customers, and new audience (or prospecting). This was critical since these campaigns didn’t allow for any of the audience inputs we typically expected.

Meanwhile, advertisers confronted with the unknown of how Advantage+ Audiences delivered their ads often chose the greater control found with original audiences. But even then, audiences often expanded. The mystery went unanswered.

And then Meta expanded access to audience segments for all campaigns that utilize the Sales objective (this feature is still rolling out). While this includes Advantage+ Shopping Campaigns, it also applies to any manual campaign that utilizes the Sales objective. And this doesn’t require optimizing for a purchase.

This new option opened up a world of possibilities for testing and transparency. I recently wrote a blog post about the test I was starting. And now I’m ready to share my initial results.

My Test

The basis of this test was simple. I wanted to use audience segments to get a better sense of how my ads were delivered when using the following targeting setups:

1. Advantage+ Audience without suggestions
2. Advantage+ Audience with suggestions using custom audiences that match my audience segments
3. Original Audiences using custom audiences that match my audience segments — with Advantage Custom Audience turned on

This was all part of a single campaign that utilized the Sales objective and a website conversion location.

Since the purchase conversion event isn’t required for this objective, I used this test to promote a lead magnet that utilizes the Complete Registration standard event.

In terms of demographics, I used all ages in the countries of the United States, Canada, United Kingdom, and Australia. These are the four countries that make up the largest percentages of my customer base.

I initially started running the ad sets concurrently before I quickly switched gears and ran one at a time without distraction. I spent a modest $270 (or so, not exact) for each ad set.

I contend a large budget wasn’t necessary for this test since my questions were answered rather quickly. My focus wasn’t on whether any of these ad sets were “successful” in terms of generating conversions. Far too many factors impact Cost Per Conversion (the ad, the offer, the landing page), and that just wasn’t a concern here.

Granted, spending thousands of dollars would give me more confidence in these results. And I’ll certainly be monitoring whether what happened here continues with my advertising in the future. But, there were very clear learnings here, even with a modest budget.

My primary concern was simple:

1. How will ads get delivered?
2. How will my budget get spent?
3. How will it be distributed between my engaged audience, existing customers, and new audience?

We have answers.

Defining My Audience Segments

A critical piece to this test is how I’ve defined my audience segments. This is done within your ad account settings.

1. Engaged Audience. These are people who have engaged with my business but have not made a purchase. I’ve used a website custom audience for all visitors during the past 180 days and a data file of all of my newsletter subscribers.

2. Existing Customers. These are people who have made a purchase. I used website custom audiences and data file custom audiences for those who have bought from me before.

There will be overlap between these two groups, of course. A Meta representative confirmed that if anyone is in both groups, they will only be counted as an existing customer.

Once these are defined, we’ll be able to use breakdowns by audience segments in Ads Manager to see results of sales campaigns for each group.

Test Group 1: Advantage+ Audience Without Suggestions

This may have been the biggest mystery of all. When you use Advantage+ Audience without suggestions, who will see your ads?

Meta gave us some clues in their documentation, indicating that remarketing was likely a big part of where delivery starts.

But this passage isn’t definitive, and I wanted to prove this actually happens — or doesn’t. Well, it happens. Boy, does it happen.

I didn’t provide any audience suggestions, yet a very large chunk of my budget was spent on remarketing to my defined audience segments. More specifically, percentages dedicated to my engaged audience and existing customers…

1. 35.4% of amount spent
2. 23.7% of impressions

That’s incredible. I never would have expected the percentages to be that high. Note that the percentage of impressions is lower because the CPM to reach my audience segments is nearly twice as high as that for the new audience.

This is a relief. While I’ve trusted in Advantage+ Audience up until now, I generally provide audience suggestions because of that small amount of doubt in the back of my mind. But, this proves that Advantage+ Audience doesn’t require suggestions to reach a highly relevant audience.

Test Group 2: Advantage+ Audience With Suggestions

This got me thinking. If Advantage+ Audience without suggestions results in spending 35.4% of my budget on remarketing to my audience segments, what would happen if I provided suggestions? More accurately, what if I provided suggestions that were custom audiences that exactly match the definitions of my audience segments?

It’s reasonable to assume that even more of my budget would be dedicated to these groups. Once again, if we were to take Meta’s explanation of how Advantage+ Audience works, that’s a reasonable explanation. Meta says that if you provide an audience suggestion, they will “prioritize audiences matching your suggestions, before searching more broadly.”

Well, here’s what happened…

So that you don’t have to do any math, here are the percentages dedicated to my engaged audience and existing customers when using audience suggestions that matched those audience segments…

1. 32.4% of amount spent
2. 29.0% of impressions

By comparison, here are the percentages when not providing any suggestions:

1. 35.4% of amount spent
2. 23.7% of impressions

So, a higher percentage (by 3%, but still higher) of my budget was spent on reaching my audience segments when not providing suggestions than when using custom audiences that matched those audience segments as suggestions. While the percentage of impressions dedicated to those groups was higher, that’s because the CPM to reach my new audience was higher with this approach.

If we hadn’t first tested Advantage+ Audience without suggestions, we’d say that this test proved that Meta did in fact prioritize reaching the audience suggestions before going broader. But, since at best there was no difference in prioritization when not providing any suggestions at all, it’s inconclusive.

My take: Audience suggestions are optional, and in some cases they are unnecessary. If you have an established ad account with extensive conversion and pixel history like I do, you probably don’t need it. In fact, it may even be (slightly) detrimental.

Test Group 3: Original Audiences Using Advantage Custom Audience

Many advertisers have chosen to use original audiences instead of Advantage+ Audience because they don’t trust the lack of transparency of algorithmic targeting. So, I wanted to test one more thing that could be proven with audience segments.

Audience segments won’t help us with better understanding ad distribution with Advantage Detailed Targeting or Advantage Lookalike. While they will help us understand how many of the people reached were already connected to us, it won’t answer questions about how much the audience is expanded — and how that compares to using Advantage+ Audience with or without suggestions.

But, we can learn a lot from how expansion works with Advantage Custom Audience. In that case, Meta should prioritize the custom audiences we provide before expanding and going broader. Technically, it may not have to go broader, and we don’t know how much broader it goes when it does.

So, I ran a test that was similar to the one where I used Advantage+ Audience with suggestions. In this case, I used original audiences and provided the custom audiences that match my audience segments. And then I turned Advantage Custom Audience on.

Here are the results…

Here’s how that breaks down by budget spent and impressions towards the original custom audiences…

1. 26.4% of amount spent
2. 24.1% of impressions

Interesting! In this case, we’d assume that the audience would expand the least and a higher percentage of the budget would be spent on the custom audiences. But, this approach actually resulted in the lowest percentage of budget spent on those groups. The percentage of impressions dedicated to those groups is about the same as when using Advantage+ Audience without suggestions.

Another point to note is that the overall CPM was highest with this approach, though it’s not much higher than when using suggestions. That’s largely driven by a higher CPM to reach the new audience.

The Results: Overall Evaluation

To recap, here are each of those ad sets in one view…

There’s no reason to split hairs here about which approach led to spending more or reaching more of my audience segments. It’s within a margin of error related to randomness that could flip if we tested again — or continued the test.

The main takeaway is this: The overall breakdown in distribution between my remarketing audience segments and new/prospecting audiences was virtually the same for each approach. It made very little difference when using Advantage+ Audience without suggestions, Advantage+ Audience with suggestions, or original audiences using custom audiences and Advantage Custom Audience turned on.

This provides strong evidence that Advantage+ Audience does exactly what Meta says it does. At least in my case, there’s strong evidence that using suggestions is completely unnecessary — or marginally impactful.

I’m also a bit surprised that using the original audiences approach resulted in as much expansion as it did. I expected delivery to hold closer to the custom audiences that I provided — at least in comparison to using Advantage+ Audience.

I didn’t want Cost Per Conversion results to be a distraction in this test because they were not a priority when evaluating distribution. But in case you’re wondering, those results followed very similar trends. Each ad set generated virtually the same number of conversions (within a range of randomness). But, Advantage+ Audience without suggestions provided the most conversions, followed very closely by the other two approaches.

Contributing Factors

It’s important to remember that while these results are generally reflective of how algorithmic ad delivery distributes our ads, they are also unique to me and how this test was set up. There are several factors that may have contributed to what I saw, and you may get very different results.

1. Budget. As I’ve said before, a lower budget still gives us meaningful information here. But, it’s reasonable to expect that the more money I spend, the less will be spent on my audience segments, audience suggestions, or custom audiences. Those audiences will become exhausted and more would likely be spent on the new audience.

2. Audience segment sizes. Very closely related to budget, but this clearly impacts the volume of results I can see from remarketing to these groups. The total sizes of these groups for my test are roughly over 200,000, but closer to 100,000 when limited by the four countries I targeted. The smaller this pool, the less can be spent there.

3. Time elapsed. It’s reasonable to assume that the greatest distribution to these audience segments and custom audiences will happen in the beginning, prior to growing expansion to new audiences. This is again related to the sizes of the audiences and the rate of exhausting them. None of these ad sets ran for a full week, so those percentages would likely drop with time.

4. Conversion event. Since I’m still in the very early stages of analyzing results using audience segments, it’s not clear how much the conversion event used for optimization impacts distribution. We know it does — Meta will make algorithmic changes to find people willing to perform the action that you want. But, it’s not clear how much the event impacts distribution to audience segments, if at all. I used Complete Registration for the conversion event here. Distribution may be different for purchases or custom events.

5. Ad account history. There’s a strong argument that can be made that I should use Advantage+ Audience and there’s no reason to provide audience suggestions. But, that doesn’t mean that’s the case for everyone. It’s possible this is viable for me because of an extensive ad account history with pixel and conversion data to pull from. New accounts, new pixels, or websites that get minimal activity may not have the same advantage. They may see much different results here.

6. Campaign construction. I went back and forth on how to run this. I didn’t run this as an A/B test because I wanted to evaluate natural distribution, rather than forcing delivery without overlap. I also chose to run these ad sets at separate times, rather than concurrently. Even though they ran separately, overlapping delivery was likely (some people may have seen the same ad from multiple ad sets). These decisions likely impacted my results.

Overall, this has been a fun test, but it’s also incomplete. These are numbers I will continue to monitor with my ads going forward to see how it plays out in the future.

Your Turn

Have you run a similar test of manual sales campaigns to see how ads are distributed for you? What did you learn?

Let me know in the comments below!

The post How Meta’s Algorithmic Audience Targeting Impacts Ad Distribution: A Test appeared first on Jon Loomer Digital.

If you’ve used Dynamic Creative to dynamically create multiple versions of your ads, you understand the basic concept of Flexible Ad Format. They function very similarly, with some minor differences.

Let’s take a closer look at what Flexible Ad Format is and how you might use it. Consider this your guide to what is becoming an increasingly important feature.

What Is It?

If you’re an old school advertiser who desires control, Flexible Ad Format may not be for you. But, if you’re able to let go of that control and lean into automation and optimization, this is a time-saving option.

Flexible Ad Format allows you to submit up to 10 images or videos for a single ad (or more when using groups). Carousel versions will also be created from the images you submitted. Meta’s ad delivery system will then automatically determine which format to show people to get the best response based on placement and audience.

Benefits

The primary benefit of Flexible Ad Format is more automation and less effort on the part of the advertiser.

In the typical scenario, an advertiser might have ad creative ideas using a single image, video, or carousel. There isn’t a preference for one format or the other, so you’d create separate ads to see how each option performs. You might also customize by placement since not all formats work with all placements.

With Flexible Ad Format, you can submit multiple images and videos for a single ad. There’s no need (or ability) to customize the ad by placement. Meta’s systems will automatically optimize the ad format to show the right version by placement and audience.

Less effort, less guessing, and more automation.

Campaign Objectives

This appears to be a bit of a moving target. When Flexible Ad Format was introduced in November of 2023, it was only available for the Traffic objective. I know because I wrote a blog post about it and found that requirement to be odd.

As of today, Meta’s documentation indicates that Flexible Ad Format is available for two campaign objectives: App Promotion or Sales.

If you use the Sales objective, make sure to toggle off “Use a Catalog” when creating the campaign. Flexible Ad Format will not be an option when this is turned on.

Also, when using the Sales objective, make sure to select either the Website or App conversion location within the ad set.

Note that the “Website and App” conversion location does not qualify for Flexible Ad Format.

Finally, there’s a bit of a contradiction as I write this. I noted at the top that this feature was initially available for the Traffic objective, but that Meta’s documentation has been updated to reflect its availability only for Sales and App Promotion. Well, I’m still able to select Flexible Ad Format when using the Traffic objective. Although, it seems to work more like Dynamic Creative.

My guess is that this is temporary while we’re in a transition period. During June of 2024, Meta began alerting users that Dynamic Creative was going away and you should use Flexible Ad Format instead.

The caveat: Dynamic Creative was only going away for the Sales and App Promotion objectives.

So, if we take Meta’s documentation literally, this is what they want us to do:

• Use Flexible Ad Format for Sales and App Promotion objectives
• Use Dynamic Creative for all other objectives

Create

Within Ad Setup under Format, select Flexible. As described, Meta will show your ad in the format they predict may perform best.

Under Ad Creative, you can upload or select up to 10 images or videos (or a combination of both images and videos).

Go ahead and upload or select a few images. Then click the Add Media dropdown again to upload or select a few videos.

When you’re done, you’ll see thumbnails for all of the images and videos you’ve selected. Click “Edit.”

You can choose to crop the images, if necessary. In most cases, you should leave this alone. The image may be cropped or expanded automatically, depending on the placement.

You can also choose to crop and trim the videos.

You may want to trim videos down to 15 seconds so that they’ll qualify for all placements.

Then add primary text, headline, description, and CTA button, as desired. Note that the multiple options here aren’t technically part of Flexible Ad Format. Text Variations is a standard option that you can use if you’d like.

Creative Groups

You may also have the ability to create ad creative groups.

Per Meta’s description:

Create up to 3 groups and organize creative elements into common themes. We’ll show each person a tailored ad from the group they’re most likely to respond to.

Each creative group can contain of up to 10 images and videos, five primary text options, five headlines, and five descriptions. You are also able to customize the URL by group.

So, in all, three creative groups could include up to 30 images and videos, 45 text variations, and three URLs. Meta suggests that you might highlight different themes or benefits for each one.

Preview Variations

You can preview all of the potential variations of your ads. You could preview all variations in the right panel. Filter by placement or format.

I find the Advanced Preview a bit easier to use since I can see more variations in one view. Click “Advanced Preview.”

Once again, you can filter by placement and ad format.

Recall that one of the formats is Carousel. Even though you didn’t create a carousel, several versions are generated for you.

Images and videos are automatically cropped or expanded to fit placements.

These previews truly are for informational purposes. There’s no way to edit or remove one of the versions, at least at this moment. I found it strange that one of the carousel options doesn’t display primary text in the preview.

If you see anything that just doesn’t look right because of the cropping or adjustment in a placement, you may need to use a different image or video that works universally.

Compared to Dynamic Creative

This is something that I’ve struggled with from the start. What’s the difference?

Let’s consider the definitions of each of these features.

Dynamic Creative:

Dynamic creative takes multiple media, such as images and videos, and multiple ad components, such as images, videos, text, audio and calls-to-action, and then mixes and matches them in new ways to improve your ad performance. It allows you to automatically create personalized creative variations for each person who views your ad, with results that are scalable.

This feature was launched in 2017 and it is turned on within the ad set. As noted earlier, Dynamic Creative is no longer available for the Sales and App Promotion objectives.

Flexible Ad Format:

The flexible ad format is designed to help you automatically optimize your ad format to show people what we predict they’re most likely to respond to based on the specific placement and audience. When you select Flexible as your ad format, you can select up to 10 images and videos in a single ad campaign, and the ad delivery system will automatically determine what media or media combination, such as single image, video or carousel, to show to people.

This feature was introduced in 2023 and is turned on within the ad. It is only available for the Sales and App Promotion objectives.

Dynamic Creative documentation also specifically mentions providing ad copy variations for primary text, headline, and description — as well as CTA buttons. Prior to Dynamic Creative, providing text variations was not an option.

Flexible Ad Format documentation doesn’t mention text. But, of course, text variations are now standard for all ads. You could technically provide 10 images and up to five text variations when using Flexible Ad Format. The focus here, though, is on the ad format.

In terms of features, there are two primary unique differences:

• Dynamic Creative allows you to select multiple CTA buttons
• Flexible Ad Format generates carousel variations based on the images you provided

Otherwise, most of the differences are subtleties, nuance, and presentation. In either case, you could use a single ad to submit up to 10 images and videos and Meta will automatically and dynamically deliver versions to get you the best results.

Viewing Results

There is official documentation from Meta on viewing results when using Dynamic Creative. Unless I’m missing something, such a page does not exist yet for Flexible Ad Format.

A breakdown by Dynamic Creative Element option is available for segmenting your results by submitted image, video, text, headline, description, or CTA button.

You should technically be able to do this when using Flexible Ad Format, too. There have been some issues getting the breakdown by image and video to work. If it doesn’t work for you, I don’t believe it is intentional — it’s a likely bug.

Another way to get deeper insight into results with Dynamic Creative is to take the following steps:

1. Click to edit your ad
2. Select “Share” below the Advanced Preview button
3. Select “Facebook post with comments”

You’ll then see comments on your top 10 combinations based on engagement.

Unfortunately, this same approach does not seem to work for Flexible Ad Format. Unlike the breakdowns, this may be intentional.

I do think that the breakdowns will eventually work. Otherwise, you will struggle to get deep insights into what image, video, carousel, or version is working best.

My Take

Whether or not Flexible Ad Format appeals to you depends heavily on your approach to advertising and what you think is important. I can see this in my feelings about it compared to what I felt about Dynamic Creative over the years.

If you demand control, you are unlikely to use Flexible Ad Format. If your goal is to find the best performing creative, this isn’t for you. If you have a deep distrust for “the algorithm,” I can’t imagine this is something that appeals to you.

If this description of a hypothetical advertiser sounds specific, it’s because that was me for about a decade. It’s exactly why I wasn’t a fan of Dynamic Creative.

But, I’m not the same advertiser anymore. My trust in Meta’s automation and optimization has improved. I now prefer algorithmic targeting over obsessing over reaching specific groups of people. And I limit my number of ad sets for things like targeting and optimization to give a single ad set more focus.

Flexible Ad Format now appeals to me because I prefer low-maintenance set up with one ad instead of multiple ads. I believe the weaknesses in automation and optimization exist, but they’re offset by the benefits.

And ultimately, I care less today about “finding a winner” with ad copy and creative than I ever have before. Instead of obsessively turning ads off and on based on small sample-sized, virtually meaningless results, I find it more efficient to give the algorithm the copy and creative and let it sort it out automatically.

That’s not a matter of right and wrong. But, I do believe that the camp you fall into will determine whether a feature like Flexible Ad Format is worth using.

How and When You Might Use It

Don’t overcomplicate this feature.

If you have very specific combinations of copy and creative that you want to use, create separate ads. That’s not the time for Flexible Ad Format.

If you have multiple relevant images and videos, but you don’t have any attachment to which are used the most or least, this is a good option for you. Especially if you have a spirit for adventure.

I’ve finally come around to Flexible Ad Format, and there are lots of reasons for that. First, it’s a matter of getting more comfortable with Meta’s automations, as described above. But, there’s also a matter of reaching the point of desperation with some advertising.

An example is that I had been trying for months, unsuccessfully, to promote my Cornerstone Advertising Tips lead magnet with ads. It was frustrating because I was getting leads for my Beginners lead magnet at a fraction of the price. But, I just couldn’t get this one to stick.

I tried multiple things. I’d give up. Then I’d come back and try something else. Eventually, I tried Flexible Ad Format.

I let go of my attachment to a single creative approach. The screenshots in this post actually feature some of the images I provided. Instead of obsessing over images, I used a filter on my phone and took a bunch of selfies.

A weird thing happened. I started seeing better results. It’s unlikely that there’s anything magical about those images. But, providing the algorithm a bunch of options and just getting out of its way can have benefits.

Your Turn

Do you use Flexible Ad Format?

Let me know in the comments below!

The post A Guide to Flexible Ad Format appeared first on Jon Loomer Digital.

Now that audience segments are available for manual Sales campaigns, it opens up all kinds of fun opportunities for testing and learning. That’s what this post is all about.

If you’re not familiar with audience segments, they’re set within your Ad Account Settings. You can define your Engaged Audience and Existing Customers.

This information can then be used to provide greater insight into your reporting. Using breakdowns, you can generate separate rows for each of these groups — as well as “New Audience” (those who qualify for neither group).

This transparency was helpful, even necessary, for Advantage+ Shopping Campaigns, which are driven almost entirely by algorithmic targeting without the advertiser’s input. These audience segments help answer questions about who is seeing our ads.

Now that audience segments are available for manual Sales campaigns, we can use this to answer some similar questions that have gone unanswered — until now.

Here are three ways you can leverage audience segments to get greater insights into your manual Sales campaign reporting. At the end, I’ll also provide some surprising results of what I’m seeing…

1. Advantage+ Audience without Suggestions

When you create an ad set that uses Advantage+ Audience, you have the option of providing an audience suggestion.

If you don’t, ad delivery will be entirely algorithmic. Meta says that their “AI uses lots of information to find your audience” — like past conversions, pixel data, and prior engagement with your ads.

Here’s a screenshot of that explanation…

That sounds a whole lot like remarketing, right? In other words, even if you don’t provide an audience suggestion, Meta’s AI should — in theory — prioritize showing ads to people you’d otherwise select to target.

I’ve long wondered whether using an audience suggestion mattered. I’ve decided that while it may not make a difference, it can’t hurt.

But, what actually happens? Does Meta’s AI prioritize remarketing audiences like their documentation claims?

Thanks to audience segments, we can test this. Define your audience segments as thoroughly as possible.

This is how I defined my Engaged Audience…

And my Existing Customers…

Next, create a Sales campaign with Advantage+ Audience without providing an audience suggestion. You will then be able to use Breakdowns by Audience Segment to see how many of the people you reached fall within Engaged Audience, Existing Customers, or New Audience.

2. Advantage+ Audience with Suggestions

We can also use audience segments to help answer our questions about whether providing audience suggestions makes a difference.

As I said in the prior section, I tend to use audience suggestions. It’s partly out of habit. But it’s also out of a belief that, at best, it can help the algorithm get started. At worst, it shouldn’t hurt.

Back to Meta’s documentation. If you provide an audience suggestion, Meta says that they will “prioritize audiences matching your suggestions, before searching more broadly.”

Again, let’s screenshot this for emphasis…

In theory, if we were to provide suggestions matching our Engaged Audience and Existing Customers, we should see Meta’s explanation above reflected in our breakdown by audience segments.

So, let’s do that! Create a Sales campaign using Advantage+ Audience. Provide audience suggestions that match your definitions of Engaged Audience and Existing Customers exactly.

The reason for this approach is simple. There’s no reason to provide detailed targeting or lookalike audiences as suggestions since we can’t use those to define our audience segments. Because of that, we’ll never know for sure whether people in those audiences saw our ads.

Since we’re told that Meta AI will prioritize our audience suggestions before going broader, we can prove that one way or another by using the exact custom audiences for suggestions that we used to define our audience segments. When we breakdown our results, we should see that reflected.

In theory, of course.

3. Original Audiences with Advantage Custom Audience

I’ve mostly abandoned original audiences (and Advantage expansion tools that go with them) since the rollout of Advantage+ Audience.

Original audiences feel like old strategies, and we should use Meta’s new and improved tools. Advantage+ Audience works in much the same way that Advantage Detailed Targeting, Advantage Lookalike, and Advantage Custom Audience, but Meta says that Advantage+ Audience is better and more advanced.

Back to Meta’s own documentation on Advantage+ Audience, this is spelled out:

Meta’s original audience options, including Advantage options (Advantage detailed targeting, Advantage custom audience and Advantage lookalike), can limit the potential of Meta’s AI which can be less effective.

Based on Meta’s own words, we assume that these work similarly, but Advantage+ Audience has the ability to go much broader (and lead to better results). So, the assumption is that if you turn on audience expansion with original audiences, the audience will expand — but your original inputs may be more respected.

Once again, we need to stick with the topic of custom audiences since these are what can be verified with audience segments. If we provide all of the same custom audiences that were used in our audience segments and turn on Advantage Custom Audience, what would happen?

How many of the people reached would be from our custom audiences? How many would be from expansion? And how does this compare to when using Advantage+ Audience?

We can test this! Once this is set up, use the breakdown by audience segment to see how your ads are distributed.

Initial Learning

I actually started part of this test already. The early results represent a small sample size, and in some cases they have been surprising.

It’s not clear how much the conversion event matters. Will your Engaged Audience and Existing Customers be used differently depending on whether you optimize for a purchase, lead, or something else?

Other factors like the sizes of the audience segments, sizes of the custom audiences used for suggestions, budget, and time may all contribute.

My initial test used a custom event for 60 second website views as the conversion event. The results were staggering. When providing audience suggestions, less than 1% of my budget was spent on them. When providing no suggestions, it was only slightly better.

But, I started a new test and the results have (thankfully) adjusted. Distribution to my Engaged Audience and Existing Customers has increased significantly, regardless of which approach I’m taking. These results have increased my faith in Meta’s claims that remarketing happens, regardless of whether you provide audience suggestions.

I’ll hold off on sharing specifics until I’m done. Until then, I encourage you to test this, too.

A Note on “Sales” Campaigns

Something that flies a bit below the radar is that you don’t technically need to optimize for purchases when running a Sales campaign. Because of that, you could run tests like I describe in this post while optimizing for any website conversion event (leads, registrations, custom events, and whatever else you use).

Sales is simply how you defined your campaign objective.

It doesn’t determine how your ads are optimized. This is defined by your performance goal and conversion event.

This is the case with Advantage+ Shopping Campaigns, too. Yes, it’s super confusing. You don’t need to optimize for SALES when running Advantage+ Shopping or manual Sales campaigns.

Your Turn

Have you run a test like this? What have you seen?

Let me know in the comments below!

The post Leverage Audience Segments for Manual Sales Campaigns appeared first on Jon Loomer Digital.

There have been several recent changes to Meta Sales campaigns that could be hugely impactful, if not transformational. It only makes sense to dedicate a post to highlight them.

In some cases, these are official changes or new features. In others, they are updates that have been spotted in the wild, but Meta hasn’t yet declared them as official changes.

Additionally, I should point out that some of these only apply to Sales campaigns while others apply to one or more other objectives.

In this post, you’ll learn about the following:

1. Audience Segments for ALL Sales Campaigns
2. A New Learning Phase
3. Scale High Performing Ad Sets
4. Schedule Individual Ads
5. Ad Sources and Site Links

Let’s go…

1. Audience Segments for All Sales Campaigns

I spotted this one when creating a Sales campaign recently, and I’m pretty excited about it.

I included the option to turn on Advantage Campaign Budget in the screenshot so that you can see that this is for a manual Sales campaign, not for Advantage+ Shopping. That’s what makes this novel.

One of the benefits of Advantage+ Shopping Campaigns is this special reporting feature. Once you define your Engaged Audience and Existing Customers audience segments, you can get deeper insights into your reporting. More on that in a moment.

There is an Audience Segments portion of your Ad Account Settings (it may be in your Advertising Settings). This is normally for Advantage+ Shopping Campaigns only, but now it explicitly states that “these settings apply to all sales campaigns in this ad account.”

You’ll need to define your Engaged Audience and Existing Customers.

Your Engaged Audience should be people who have engaged with you but have not bought. I use my email list and website visitors to define this group. Do not worry about excluding people who have purchased from you (I’ll get to that in a minute).

Your Existing Customers are those who have bought from you. I use specific website custom audiences and email segments to define this.

If a person is found in both audience segments, they will only be considered among Existing Customers.

Now, here’s what’s so great about it. One of the potential issues with Advantage+ Shopping Campaigns is that since targeting is entirely algorithmic (you don’t provide targeting inputs), there can be a lack of trust regarding who sees your ads and how they’re delivered. Once you define these groups, you get transparency in your reporting.

When you use the Breakdowns dropdown menu and select By Demographics > Audience Segments…

…you’ll get a separate row for Existing Customers, Engaged Audience, and New Audience.

Back to manual Sales campaigns. This same transparency was needed when using Advantage+ Audience or any of the Advantage audience expansion products. How much is spent on reaching my remarketing audience? How much is spent on existing customers? How much on prospecting to completely new people?

This will not only give you a breakdown of how your money is spent, but where the results come from. That’s insanely helpful.

I’m still holding out hope that Meta will eventually make this available for all campaign objectives. It’s necessary.

2. A New Learning Phase

There are actually two changes related to the Learning Phase that advertisers have spotted recently that could be enormously helpful.

You’re probably familiar with the Learning Phase as the period of time, after publishing a new ad set or making a significant edit, when Meta’s ad algorithm is learning how best to deliver your ads for optimal results.

Typically, that has meant needing 50 optimized actions within a seven-day period (usually the first seven days since publishing). If you are unable to reach that volume, you’ll find yourself in “Learning Limited,” which may prevent you from getting optimal results.

While this might be reasonable for most actions, it’s going to be difficult for the typical brand or advertiser to get 50 conversions in a week when that conversion is a purchase — especially if it’s a high value purchase. As a result, advertisers either avoid optimizing for purchases or they get what is likely sub-optimal results.

That could be changing. Many advertisers have reported seeing a new Learning Phase that requires 10 conversions in three days.

This is huge. While the window is shortened, this only requires getting a little more than three sales per day — rather than the seven that were required previously. If you struggled to exit the Learning Phase in the past, this gives you a very reasonable chance now.

Note that I haven’t seen anything indicating that this is an official change yet. As I type this, Meta’s documentation still reflects the need for 50 conversions. But, this is at least a test.

I should also note that I’ve noticed some of my ad sets never enter the Learning Phase at all now. They immediately enter Active status. It’s not clear to me when or why this is the case, but it seems that the Learning Phase is much more forgiving now and may require less data to exit than it once did.

What’s happening here? Why is it that the Learning Phase is shortening — and in some cases not happening at all? This appears to reflect that Meta has more or better data to more quickly determine how to optimally deliver your ads. This is more than likely related to improved machine learning and AI.

3. Scale High-Performing Ad Sets

The Learning Phase is the source of a great deal of frustration, and even fear, among advertisers. They’re reluctant to make any significant changes, including scaling the budget, because it may restart the Learning Phase.

The reason for that frustration is that “learning” typically means unstable and less predictable results. If you’re getting great results that are consistent from day to day, it’s reasonable to not want to rock the boat.

Well, one of the updates allows you to increase your budget without restarting learning. If you ever see “High Performing” in the delivery column of an ad set, it qualifies for budget increases that immediately return to Active.

Meta will even give you a scale of recommended increases and the projected number of results you should expect.

While you’ll see diminishing returns the more you spend, it’s good to know that you won’t see any negative impact to the stability of performance.

This added transparency should help advertisers better plan their ad spend and take advantage of high performing ad sets without the fear of restarting the learning phase.

4. Schedule Individual Ads

Normally, the schedule to run your ads is determined within the ad set. This means that your ad schedule applies to all ads within it. But, you can change that with a new update that is rolling out.

When you create a manual Sales campaign with the Website conversion location, you may see a “Show More Options” link below Multi-Advertiser Ads within the Ad Setup section.

Click it and you’ll see a “Schedule” option.

Hover over this area to get the option to edit. You can then set a start and optional end date for your ad.

The ability to schedule individual ads was previously a unique option found within Advantage+ Shopping Campaigns. But, now we’re seeing this surface in manual Sales campaigns, too.

This allows you to schedule individual promotions for ads rather than manually stopping and starting them or creating separate ad sets. If you created an ad set to promote a specific product, you could schedule an ad that reveals a sale price that coincides with a promotion. This could especially be helpful for seasonal promotions, like during Black Friday and Cyber Monday.

There are many ways you might use this. You could conceivably create an ad set that promotes various similar products, but schedule when each product gets promoted.

5. Ad Sources and Site Links

Meta is rolling out the ability to include links to other important information under your ad creative. The end product looks like this…

Notice the scrollable links below the ad creative? Those are controlled by the advertiser.

The following settings are required:

• Sales, Traffic, Engagement, or Leads objective
• Website conversion location
• Manual upload using single image or video

Within ad creation, you should see an Ad Sources section.

You can optionally provide a website URL and Meta will automatically attempt to source some site links.

Click “Review and Confirm.” You can review the site links that Meta found.

In the example above, Meta automatically pulled links to two of my products and three subscriptions. While they are great suggestions, Meta also uses the full page title, which I wouldn’t want to use.

Click “Set Up Manually.”

You need at least three site links to display them on your ad. Include a display label and URL. When you’re done, click Save.

You should then see confirmation that the site links were added.

You can also use your product catalog to display individual products or categories of products.

You can view what this will look like by pulling up the Advanced Preview and filtering by Advantage+ Creative enhancements. There should be one for “Add Site Links.”

How should you use site links? Meta has a recommendation:

You can use the site links feature to highlight different categories, products, deals, sign-ups, and your other most visited landing pages within one campaign. Ads with site links can help provide more opportunities for people to learn about your business, products, and services and achieve conversions more easily.

Don’t feel like you need to be boxed in by this recommendation as a guideline. Get creative.

Something that immediately came to mind for me was promoting blog posts and videos on my website. Normally, the entire focus is getting that traffic and engagement. But, now I can add site links to get a secondary registration or purchase because it’s highlighted in the ad.

Something that isn’t yet clear to me is how easily conversions from site links can be tracked to these ads. It’s like any other situation related to attribution, except that the “results” won’t necessarily be tied to the site links. This is where adding extra columns for execution of conversions related to your site links could be necessary.

Your Turn

Lots going on right now, and these are all some pretty amazing updates for Meta Sales campaigns. Do you have any favorites?

Let me know in the comments below!

The post 5 Big Updates to Meta Sales Campaigns appeared first on Jon Loomer Digital.

CPM (Cost Per 1,000 Impressions) may be the most impactful and frustratingly erratic metric when it comes to your Meta ads performance. How much it costs to reach people can override the greatness — or terribleness — of your ads.

Some of the choices you make will contribute to CPM in a positive or negative way. But, other factors can result in temporary or random CPM spikes that can lead to a misunderstanding of performance.

I’ve been guilty of this, too, and it led to this blog post. I want you to avoid this mistake while understanding how this sometimes invisible force can impact performance — and the perception of performance.

Example

I ran a lead generation campaign for two months to promote my Beginner Advertiser lead magnet that was reasonably efficient at $2.24 per lead. The problem was that the lead magnet it promoted wasn’t for my optimal audience.

I offer a Beginner Advertiser email sequence because it’s something to get people started. But given the choice, I’d prefer to promote one of several other lead magnets that appeal to the intermediate to experienced advertiser.

Unfortunately, I’ve struggled to get the same results lately with these other lead magnets. Leads often cost at least twice as much as those for the Beginner offering. Knowing that, I often abandon these campaigns rather quickly and go back to the one I know works.

The latest example is a lead magnet for my Cornerstone Advertising Tips. What I love about this lead magnet is that it is a much longer commitment. While the Beginner offering is over after eight quick emails, Cornerstone is a weekly tip that will go for several months. It’s also much more advanced than the option available for beginners.

I’ve spent more than $200 to promote Cornerstone so far, and the results just aren’t close. I’m spending $5.41 for these leads, which is more than twice what I pay for beginners.

The assumption was that the offer for Cornerstone just isn’t as appealing to a wide-ranging audience the way Beginners is. I’d likely need to spend more time on the ad copy and creative to improve it, but that CPA gap may be too much to overcome.

But, once I started scratching below the surface, it became a bit less discouraging. It didn’t take long to realize that there was nothing wrong with this lead magnet. The cost discrepancy could be traced almost entirely to CPM.

As you can see in the example above, the difference in costs isn’t due to the offer or conversion rate. An impression for the Cornerstone offering is more likely to produce a lead (.59%) than an impression for Beginners (.41%). In each case, about 1% of those reached became a lead.

The biggest difference here is CPM. It costs 3.2 times more to reach people when promoting Cornerstone than when promoting Beginners.

Note that both ad sets utilize nearly identical settings:

• Optimized for Facebook Leads from Instant Forms
• Advantage+ Audience with a few custom audience suggestions
• United States, Canada, United Kingdom, Australia
• Advantage+ Placements

So, what’s causing this? I have a theory, but I’ll get to that later.

First, let’s dig a bit deeper into the various factors that contribute to CPM — both within and outside of our control.

Are You Driving Up CPM?

First of all, know that there are several ways that you can drive up CPM and make things more difficult for yourself.

1. Targeting Restrictions.

If you choose to forgo Advantage+ Audience in favor of original audiences, you’ll have the option of further limiting your potential audience.

When custom audiences are provided with Advantage+ Audience, they are only used as an audience suggestion.

But, if you provide a custom audience when using original audiences, you can choose to limit targeting to those people only.

Additionally, detailed targeting and lookalike audiences are used only as suggestions with Advantage+ Audience. In some cases, you can limit targeting to those inputs when using original audiences (in other cases, the audience may be expanded).

Of course, those who choose to use original audiences do this so that the audience can be restricted. But, that restriction also limits the algorithm, which often drives up CPM.

2. Demographics

When using Advantage+ Audience, only an age minimum set in Audience Controls is considered a hard constraint. Otherwise, gender and age ranges are considered audience suggestions and the algorithm can go where it needs to go to find your desired action.

If you switch to original audiences, you can prevent ad delivery to people outside of your age range and gender inputs. While this provides more control, it applies a restriction to delivery.

There are cases when limiting demographics can make sense. But, many advertisers assume it’s necessary when it’s not. That assumption can drive up CPM.

3. Geography.

There’s no secret that some countries are much more expensive than others to reach due to advertiser competition. I primarily target the United States, Canada, United Kingdom, and Australia knowing that it will cost more to reach people there, but there tends to be an acceptable tradeoff. You may not have a choice here, but the countries you target will impact CPM.

Some geographical decisions are avoidable, though. If you choose to limit your audience to certain regions, states, or cities, that limitation restricts your potential audience size. While you might have a good reason for this, expect a higher CPM.

4. Placements.

Meta wants you to use Advantage+ Placements, which makes all placements available for delivery. If you want, you can manually remove placements, which will limit potential options for the algorithm.

Sometimes it makes sense to remove placements to prevent the algorithm from finding low-quality actions that can happen in specific locations. But in other cases, you may do this unnecessarily and hurt performance.

5. Estimated Action Rate.

One of the factors that impact your performance in Meta’s ad auction is the Estimated Action Rate. This is the estimate of the probability that a person will engage with your ad. A high Estimated Action Rate could help you win the auction with a lower bid. A low Estimated Action Rate could have the opposite effect.

Essentially, this is all about creating ads that inspire the action that you want. If you don’t do this well, you can drive up CPM.

6. Low-Quality Ads.

Another factor that contributes to auction performance is ad quality. This has nothing to do with Estimated Action Rate. Instead, Meta uses signals from users to detect click bait, engagement bait, and other signs of low-quality ads that push the lines of the ad policy. Low-quality ads will lead to higher CPM costs.

Uncontrollable Factors

While your micromanagement of an ad campaign can drive up CPM costs, there are other factors that are completely outside of your control. While you could conceivably include industry in the mix here, I want to focus on things that are variable from day to day or week to week (your industry tends to be static).

1. Competition.

The more money in the system looking to target the same audience you want to reach, the higher your costs can go. This can be due to seasonal competition, and tends to be reflected in spikes beginning before Black Friday and dropping after the new year.

But, there can also be completely random competition increases as well since you don’t control what other brands and advertisers choose to do.

2. Learning Phase.

Ad delivery and performance are least stable during the Learning Phase. You’ll often see this reflected in an inflated CPM during this time. Even when my ads never enter learning, I’ve found that CPM tends to be higher during the initial days of the ad set.

3. Randomness.

Sometimes you just can’t explain it. CPM costs can rise and fall for no particular reason. More accurately, there’s certainly a complicated reason that combines several factors that mostly happen behind the scenes, but you won’t always have a clear reason to explain it.

In other words, you shouldn’t obsess over CPM since there’s always going to be a randomness to it that is unpredictable and can’t be controlled.

CPM is a Secondary Metric

CPM is an important metric, we can’t deny that. As you saw with my example at the beginning of this post, you can have everything else go right, but an inflated CPM can drastically alter your perception of a campaign. The opposite can happen, too. Maybe your campaign and ads are nothing special, but a low CPM can get you great results.

All this said, we can’t treat CPM as a primary metric. It’s not a Key Performance Indicator (KPI). In most cases, don’t make drastic changes to your advertising in an effort to lower your CPM.

The exception, of course, would be if you are otherwise restricting ad delivery in ways that you shouldn’t, and your micromanagement is driving up CPM. If you’re limiting ad delivery by demographics or placements, or using original audiences over Advantage+ Audience, it’s worth trying a more hands-off approach.

But, changing your performance goal or targeting the cheapest countries in an effort to get your CPM down is unlikely to get you better results. A lower CPM does not guarantee an acceptable Cost Per Action. It will be up and down, and it’s mostly best to understand that it’s a factor that is mostly outside of your control.

My Theory

Back to my example at the top. The one benefit of looking at CPM in that case is that it reassured me that I wasn’t necessarily doing anything wrong. It wasn’t a matter of people preferring the Beginner offer over Cornerstone. People were telling me (through their action rate) that they liked it just fine.

As noted, the setup of the Beginner and Cornerstone ad sets were nearly identical. Both used Advantage+ Audience with similar audience suggestions. Both used the same performance goal and left Advantage+ Placements on.

My theory is that because all performance indicators are positive, I just need to be patient. I’ve started, stopped, and tried again with two different ad sets so far that totaled four days and $200 in ad spend. While those early results seemed bad on the surface (which led me to make that first decision to turn it off), I need to let it keep going.

Strangely, the Learning Phase does not apply here. I don’t believe it was ever on. But, that doesn’t necessarily mean that my ad set will immediately deliver optimally.

I decided to go back and look at results at several of my ad sets during the first week compared to its overall average, and I found a common trend: CPM almost always starts high and trends downward after the first few days or week.

The other possibility is that the build-up to Memorial Day Weekend contributed to increased competition. I think it’s possible this is a minor factor, but I have my doubts that it’s the primary driver.

Your Turn

Have you seen that CPM impacts ad performance? What do you do about it?

Let me know in the comments below!

The post Meta Ads Performance and the Impact of CPM appeared first on Jon Loomer Digital.

It’s a common problem. Meta advertisers, in search of the perfect combination of advertising strategies, overcomplicate things and make it worse. Several factors contribute to this problem.

First, we assume that “complicated” means “better” and “sophisticated.”

How could an Advantage+ Shopping Campaign with no targeting inputs and one ad set perform better than my execution of a 10-step strategy with multiple campaigns, ad sets, and audience segmentations?

Second, our answer to fixing a campaign that isn’t working as we’d like is to tweak, add, and add some more. Duplicate the campaign, create a new ad set, try a new optimization, or target a new group.

It’s not that the simplest strategy is always the best. But, less complicated strategies provide more clarity. By simplifying, you aren’t driving up your costs by competing against yourself or restricting the algorithm. If something isn’t working as well as you’d like, the focus is on ad copy and creative, your offer, and your website.

Look, I was once the king of complicated strategies. My favorite thing to do was create complex Evergreen Campaigns that used 10 ad sets to move a very small number of people through an ad funnel. But, things have changed.

Some advertisers are stuck in the past. Others are frustrated with their results and are trying everything. And we listen to far too many “gurus” with complicated strategies that sound good because of their complexity.

Limit Unnecessary Complexity

Don’t take every recommendation in this post as gospel. There are too many factors that contribute to performance to decide that one human’s advice is best for everyone.

I’m not always right. Sometimes there’s nuance. And even my advice below should be taken as a general approach. I don’t want you to always do what I suggest. I just want you to think about these things.

Your main takeaway should be this: Make a conscious effort to limit unnecessary complexity.

“Complex” is rarely helpful. By adding more variables, you make it more difficult to understand what is working and what isn’t. You’re watering down your results. It’s difficult to know what you need to change to get things back on the right track.

Complexity can be created by adding campaigns or ad sets. It can result from micromanaging targeting or placements. It can even be found in testing your ad creative.

It’s not that you should never do these things. But, before you do, ask yourself whether it’s necessary. Is it truly helpful?

There are always exceptions to what I recommend below. It could be due to large budgets, specific company goals, or unique circumstances. I get it. Sometimes you can’t avoid it. But, understand why “simple” is often better.

Let’s discuss the main things that you can simplify…

1. Campaigns

I host regular one-on-ones and help clients think through their advertising. One of the first things I often see is an Ads Manager cluttered with a whole bunch of campaigns.

Campaigns for sales, leads, traffic, engagement, and awareness. Multiple campaigns for a single objective.

There are only two objectives that I would recommend are required for virtually every business:

1. Sales
2. Leads

If we really want to simplify things, an Advantage+ Shopping Campaign is often the best way to run a sales campaign. No targeting and one ad set. All of the focus is on your ads.

Regardless, focus on sales and leads — or on conversions of some kind. Everything else is extra and needs a good business reason for doing it. Top of funnel objectives are rarely worth the money because Meta doesn’t have a way to optimize for quality traffic or engagement. Instead, you’ll typically get a bunch of empty clicks.

Save the money you were going to use on those top of funnel campaigns and push them towards leads or sales. You will build awareness, engagement, and traffic incidentally with those campaigns.

Also make sure you actually need the multiple sales or leads campaigns before you create them. If you have specific business goals, multiple campaigns can be difficult to get around.

Just remember that the more campaigns you create, the more ad sets you create. And that can eventually become problematic, in the form of Auction Overlap, which can drive up your costs.

2. Ad Sets

This is connected to limiting your number of campaigns, but also not. If you create 20 campaigns, that’s at least 20 ad sets. That, by itself, could be a problem.

But, you could also have two campaigns that each house 10 ad sets. Maybe this is an exaggeration, but advertisers do it. In most cases, it’s completely unnecessary.

If you create multiple ad sets to segment your audience, for example, you are contributing to Audience Fragmentation. This makes your ad spend less efficient.

You can’t always avoid creating that extra ad set. But, whenever possible, aim to consolidate.

3. Targeting

Since targeting is the primary motivator for advertisers who create multiple ad sets, this is a good transition.

Targeting may be the best example of how advertisers overcomplicate things. While it made sense in the past, it almost never does now.

If you’re optimizing for some sort of conversion, you should use Advantage+ Audience (assuming you haven’t created an Advantage+ Shopping Campaign). Provide some audience suggestions and allow the algorithm to do its thing.

There’s no need to create multiple ad sets to test the use of different audience suggestions. Those suggestions are unlikely to be all that impactful anyway. They’re just a starting point. Once the audience expands, those multiple ad sets will be nothing but overlap.

If you prefer original audiences over Advantage+ Audience due to the perception of additional control, keep in mind that your targeting inputs are often expanded:

• Advantage Detailed Targeting and Advantage Lookalike are automatically on and can’t be turned off when optimizing for conversions
• Advantage Detailed Targeting is automatically on and can’t be turned off when optimizing for link clicks or landing page views

The audience is often expanding anyway.

Also, don’t assume that expansion is bad and needs to be avoided. While eliminating expansion can lead to good temporary results, it’s not scalable. You can’t, for example, keep targeting your email list and website visitors while spending $100 per day and expect to get good results beyond a short window.

Remarketing is mostly dead. First, the algorithm is smart enough now that it will automatically target people based on your conversion history, pixel data, and prior engagement with your ads. This is even the case when you don’t provide targeting inputs with Advantage+ Shopping or Advantage+ Audience.

I will still use my remarketing custom audiences as suggestions for Advantage+ Audience. Even then, I don’t know how much it matters. But, it gives me peace of mind that it’s at least starting with that group.

Simplify your targeting. Embrace the fact that your targeting inputs are far less impactful than they were in the past. Stop obsessing over isolating the perfect combination of demographics, detailed targeting, and lookalike audiences. Ditch creating multiple ad sets for the purpose of audience segmentation.

Don’t lose any sleep over it. This is a good thing because it allows you to focus on your copy and creative.

4. Budget

All of these things are related.

The vast majority of advertisers have a finite budget. You can’t spend more than a certain amount per day or month.

And yet, you’re spreading that budget across a cluttered list of campaigns and ad sets — many of which are unnecessary. You complain about bad results and your inability to exit the learning phase. And the whole time, this problem is easily solvable.

Create fewer campaigns. Create fewer ad sets. But spend the same amount. Consolidate your budget that was spread across campaigns and ad sets into fewer targets.

This will give you the best chance of spending enough to help the algorithm learn and generate optimal results.

5. Performance Goals

Your performance goal may be the most important part of the campaign creation process.

I know, the ad copy and creative are incredibly important. But, great copy and creative may not overcome the wrong performance goal. If you use the right performance goal, mediocre ad copy and creative could still get you acceptable results.

The performance goal is exactly that: It defines what you are trying to accomplish. This helps Meta know how to deliver your ads and who should see them. It helps determine whether your ad set is working or underperforming and something needs to be corrected.

What’s crazy to me is that this shouldn’t be complicated, but advertisers love to complicate it.

As discussed earlier, your priority should be to optimize for conversions of some kind. You can set a performance goal to Maximize Conversions or Maximize Value of Conversions.

And then define what exact conversion type is most important to you. It could be purchases, leads, complete registrations, or potentially something else.

The algorithm will then focus on getting you those conversions. It wants to make you happy.

But, don’t get cute.

If you optimize for link clicks or landing page views, the algorithm will be focused on getting you link clicks or landing page views. They could be accidental clicks, bots (before detected), or people who click on everything. But, these people may not have any interest in your ad or your product.

If you optimize for ThruPlay, the algorithm will find ways to get people to watch at least 15 seconds of your video. That includes prioritizing placements where users are forced to watch video ads and can’t skip them. You assume these people cared about your video, so you create remarketing campaigns to target them. But, many didn’t care.

Keep it simple: Set a performance goal that defines exactly what you want.

This is the only way that you and Meta’s ad delivery algorithm will be on the same page. You can’t complain about low-quality traffic if you didn’t define you wanted high-quality traffic. You can’t complain about not getting purchases if you told the algorithm you wanted add to carts.

6. Bidding

The ad auction is dependent on three things:

1. Your bid
2. The likelihood that someone will engage with your ad
3. Ad quality

Unlike the typical auction, your bid isn’t everything. The highest bidder doesn’t necessarily get the impression. And really, you don’t want that to be why you win the auction anyway.

If you don’t touch anything, Meta bids for you. In most cases, it’s using the Highest Volume bid strategy. Meta’s focus will be to get you the highest volume of optimized actions within your budget. If you optimize for Value, the Highest Value bid strategy is default.

Otherwise, you can use a Cost Per Result Goal, ROAS Goal, or Bid Cap.

But, in most cases, don’t bother. You’re usually going to be disappointed. You’re not going to get magical results because you set a Cost Per Result Goal of $.01 and Meta unearths people willing to buy your product at a penny per purchase.

More often than not, your manual bidding will lead to spending less of your budget and getting fewer or worse results. It’s not that you should never try manual bidding. But, it should mostly be used as a last resort when you can’t get anything else to work.

7. Placements

If your only active ad sets are optimized for some sort of conversion, this is the easiest step possible. Do nothing. Keep your hands off and use Advantage+ Placements.

It’s not that there aren’t low-value placements. Audience Network is notorious for generating low-quality clicks and video views. But, if you’re optimizing for conversions, the algorithm knows about these pitfalls, too. You can bet that very little, if any, of your budget will be spent there.

Not, of course, unless that placement leads to conversions. And to be clear, impressions that don’t lead to a direct conversion can have value, too. One user may see three or five ads before finally converting. Some of those lower-performing (and lower-priced) placements may contribute.

Where you need to be careful is when optimizing for anything other than conversions. As we know, Audience Network leads to low-quality clicks. And since you can’t set a performance goal of high quality link clicks or landing page views, Meta will fill your results with those clicks if you set a performance goal of link clicks or landing page views.

A similar problem is found in Audience Network Rewarded Video when optimizing for ThruPlay. Third-party apps monetize themselves with Meta ads for this placement. People can watch videos in exchange for virtual currency that is used in the app. These people don’t care about your video.

Of course, there are other examples. But, this is another reason why optimizing for anything other than conversions is a complicated game of whack-a-mole. You need to do all you can to control quality, and that includes removing problematic placements.

But, again, that’s not an issue when optimizing for conversions. Keep it simple and use Advantage+ Placements.

8. Ad Copy and Creative

Ad copy and creative are super important. If they aren’t the most important part of your advertising, they’re at least in the discussion.

But, you don’t need to overdo this.

Meta says that there’s no benefit to creating more than six ads for a single ad set. And if your budget is low, even those six will chop up your budget to the point of making results mostly meaningless.

As I’m sure you know, the algorithm will pick one or a handful of those ads rather quickly and run with them. This isn’t because those ads were clearly more effective at a high level of certainty, it’s because the difference is negligible and the algorithm had to run with something.

Create multiple ads if you have multiple ad ideas. But, don’t feel you need to create six. And don’t obsess over the results and what they mean from small sample sizes.

Sometimes, it’s best to create two or three ads and run with them. Not getting great results? Fine. Create two or three more. It doesn’t matter that you restart the learning phase because you weren’t satisfied with your results anyway.

9. Testing

I don’t want to completely minimize testing because it can be helpful. But, I also see advertisers stuck in a constant cycle of A/B tests that barely move the needle.

Over-testing happens when you don’t trust anything that Meta does automatically. You feel the need to scientifically define absolute winning ads and optimizations.

But, the testing itself costs money. Performance is almost always worse when you force the algorithm to A/B split the audience. And you’re not guaranteed to get results that are statistically significant that would have made the test more productive than simply running the ads the old fashioned way.

Again, there are exceptions. If you’re going to run a long-term campaign, testing ads makes sense. And if you have big budgets, knock yourself out.

But, these low-budget tests to find winning creative are virtually meaningless. Just run the ads. Let the algorithm sort it out.

You can “test” without always needing to find a winner. Give the system multiple ads to work with. Utilize Dynamic Creative or the text variations feature.

Once again, complicating things with a test isn’t always the best path to profitability. Sometimes the simplest approach is the answer.

10. Reporting and Interpretation of Results

What’s a good CPC for this industry? Is this an acceptable CTR? Why is my CPM so high? How can I get it down?

Just stop…

Meta offers limitless metrics that can distract you. Many of them provide some value. But don’t obsess over the secondary metrics.

Keep it simple. Focus most on your goal action and the cost per goal action.

Not getting the cost per goal action that you’re wanting? The secondary metrics can help tell that story. Maybe your conversion rate is great, but the CPM is going up due to competition. Or maybe the CTR is lower than normal, indicating that you need to improve your offer to get people to click. Or those secondary metrics are all solid, but you aren’t getting conversions — so you shift your focus to the landing page.

Stop freaking out about every metric. They’re all part of the story. But, only a couple truly matter. The rest are window dressing.

Your Turn

How have you overcomplicated your ad strategy?

Let me know in the comments below!

The post A Simplified Meta Ads Strategy for Optimal Results appeared first on Jon Loomer Digital.

The process of Meta ad targeting and audience selection has evolved significantly during the past few years. Advertisers have been pulled through audience expansion and into complete algorithmic targeting, largely against their will.

But, there are very good reasons why these changes, which come at the expense of advertiser control, were necessary. It started with regulatory pressure on Meta related to the misuse of targeting distinct groups in order to manipulate elections or discriminate. You could also point to a loss of reliable data due to changes in allowable tracking used for targeting.

And finally, there’s a matter of Meta’s own investment in AI and machine learning. There are times when Meta may be better at finding your ideal audience automatically than you could be manually.

These days, we’re given options. Advantage+ Audience is the default method for audience selection, but you are able to switch to Original Audiences.

Not without repeated warnings, of course…

It would be a lot easier if I could tell you to either always use Advantage+ Audience or always avoid it. It’s not that simple.

There are times when Advantage+ Audience makes the most sense. There are times when it’s probably a bad idea. But, most advertisers misunderstand when to take each approach.

It’s understandable why there’s so much confusion. Several variables apply. While Advantage+ Audience is rather straightforward, Original Audiences behave differently depending on your performance goal.

Once you better understand how each of these work, the strengths and weaknesses will begin to clarify. By the end of this post, I hope that you’ll have a better plan for when you should use Advantage+ Audience and when you should revert to the old ways.

How Advantage+ Audience Works

For each approach, let’s focus on what you can restrict, the inputs you can provide, and when Meta can expand targeting beyond your initial inputs.

Restrictions:

Audience Controls provide limited restrictions regarding who can see your ads.

Your ads will not be shown to people outside of your selected locations, minimum age, languages, or excluded custom audiences.

Note that there is not an Audience Control for maximum age or gender. Your ads will be shown to anyone who is likely to perform your goal action.

Your Inputs:

Your inputs are Audience Suggestions and they are not required. Suggestions can include custom audiences, lookalike audiences, age range, gender, and detailed targeting.

Note that these are all suggestions and not restrictive. Ads can be shown to people outside of your selected custom audiences, age range (assuming it’s within the age minimum Audience Control), gender, and detailed targeting.

If you don’t provide suggestions, Meta will begin with your pixel data, conversion history, and prior engagement with your ads while searching for people most likely to perform your goal action.

Expansion:

I don’t know if defining what Meta does here as “expansion” is accurate, but it’s a way to compare Advantage+ Audience with what can happen using Original Audiences.

Meta will initially prioritize your audience suggestions before going much broader. Ultimately, the algorithm will show your ad to anyone (assuming this is allowed by Audience Controls) if they are likely to lead to more of the action you want, as defined by the performance goal.

How Original Audiences Work

Original Audiences allow you to use targeting the way you “used to” use it — but not the way you did it several years ago. It just provides more control than Advantage+ Audience, though there are several variables that alter how it works.

Restrictions:

Meta will not deliver your ads to people outside of your selected locations, age range, gender, exclusions (custom audience or detailed targeting), or languages.

There are signs that detailed targeting exclusions may be going away, but Meta is currently saying that there are no immediate plans for such a change.

Your Inputs:

In addition to the audience inputs listed above in Restrictions, advertisers can provide custom audiences, lookalike audiences, and detailed targeting.

Expansion:

This gets somewhat complicated with Original Audiences. In some cases, Meta can serve your ads beyond your selected detailed targeting or lookalike audiences, and you can’t turn it off. Sometimes you have the option. And whether or not you have an option may be different, depending on your version of Ads Manager.

Advantage Custom Audience: When you provide a custom audience or group of custom audiences, you have the option to turn on Advantage Custom Audience. When on, your ads can be delivered to people beyond your selected custom audiences if it will lead to better results.

There is always an option to turn Advantage Custom Audience off when using Original Audiences, regardless of the performance goal.

Advantage Lookalike: Lookalike audiences allow you to create a pool of people who are similar to those who are connected to you in some way. When creating these lookalike audiences, you can focus on those who are within the top 1 to 10% of those most similar within a given country or group of countries.

When you provide a lookalike audience for targeting, Advantage Lookalike allows Meta to show your ads to people outside of your selected percentage if it will improve performance.

This cannot be turned off when optimizing for conversions.

Advantage Detailed Targeting: Advertisers can target people based on interests and behaviors on and off of the Meta family of apps using detailed targeting. Advantage Detailed Targeting allows Meta to reach people beyond those inputs if it will improve performance.

Similar to Advantage Lookalike, Advantage Detailed Targeting is on by default and cannot be turned off when optimizing for conversions.

While it appears to be Meta’s plan to make this the default when optimizing for link clicks and landing page views, it’s not currently the case for all advertisers.

A Summary of Control

There are multiple reasons to favor one approach over the other. For many advertisers, it’s a matter of control, even though that complaint isn’t always justified as a harm.

Let’s summarize the level of control for each approach…

Advantage+ Audience

Controlled:

• Locations
• Minimum Age
• Languages
• Excluded Custom Audiences

Audience Suggestions:

• Custom audiences
• Lookalike audiences
• Age range
• Gender
• Detailed targeting

Original Audiences

Controlled:

• Locations
• Age Range
• Gender
• Languages
• Excluded custom audiences

Optional Expansion:

• Advantage Custom Audience
• Advantage Detailed Targeting (all but for conversions, link clicks, and landing page views)
• Advantage Lookalike (all but for conversions)

Forced Expansion:

• Advantage Detailed Targeting (for conversions, link clicks, and landing page views)
• Advantage Lookalike (for conversions)

As a reminder, not all versions of Ads Manager have forced audience expansion when optimizing for link clicks and landing page views, but Meta announced this as a change.

When to Use Advantage+ Audience

Advantage+ Audience leverages algorithmic targeting, putting minimal limits on whom can be reached in an effort to get you the most desired actions at the lowest cost.

The assertion that Advantage+ Audience leads to lower costs is difficult to dispute (or prove false). The question is related to quality.

When you should use Advantage+ Audience can be summarized like this…

1. When optimizing for purchases. You could make the argument that you should instead use Advantage+ Shopping Campaigns, but Advantage+ Audience is a good option as well. The algorithm can’t be misled by low-quality purchases, since this isn’t a thing. It will do what it can to get you the most purchases at the lowest cost. If you desire higher value, you can optimize for Value instead.

2. When optimizing for other types of conversions. There is a caveat here since quality is something to monitor. But, I’ve found Advantage+ Audience to be plenty effective for running lead campaigns. When quality is a concern, you can also assess your lead forms or optimize for Conversion Leads instead.

When to Use Original Audiences

Choosing to use Original Audiences is less about leveraging a unique strength of this approach and more about avoiding a potential weakness associated with Advantage+ Audience. But, let’s be clear: Original Audiences merely help limit the issues associated with certain types of optimization.

1. Top of Funnel Optimization. Whenever possible, you should select a performance goal that is near the bottom of the funnel (conversions or leads). The algorithm’s focus is getting you as many of those actions as possible. But, if you optimize for link clicks, landing page views, post engagement, ThruPlay, or some other type of top of funnel action (and you have no choice), you should use Original Audiences.

Top of funnel optimization is already problematic because the algorithm does not care about generating quality link clicks, landing page views, post engagement, or ThruPlays. Its only focus is getting you that thing, regardless of who is performing the action. This is why Advantage+ Audience can make what is already a problem even worse.

Original Audiences allow you to put some guardrails on your targeting. You can isolate gender, age ranges, and even lookalike audiences and detailed targeting. Of course, if you have the update that forces audience expansion for link click and landing page view optimization, it’s less restrictive.

Keep in mind that having customers who are primarily a certain gender or within a specific age group isn’t enough to require Original Audiences. If you optimize for purchases, use Advantage+ Audience — the algorithm will focus on those most likely to purchase. But, this customer focus is more reason to switch to Original Audiences for the top of the funnel (though you should have made that switch anyway).

2. Remarketing. If you want to run ads that only reach people within a custom audience, Advantage+ Audience is not the method for you. The custom audience you provide will only be used as an audience suggestion. You should instead use Original Audiences.

The question is whether you need to run a “true” remarketing campaign. Some advertisers run general remarketing campaigns to their email list, website visitors, or people who engage with their ads because they assume these people are more likely to act on their ads. If that’s the case (and you’re optimizing for conversions), I still recommend using Advantage+ Audience and listing custom audiences as suggestions.

The only time when using Original Audiences for remarketing would be necessary is if you have a unique message that only people in that audience should see. Original Audiences will allow you to isolate that group.

Have a Reasoned Approach

I hope this post provides some clarity on how these two approaches work and when you might use both. Find what works for you. But, I ask that you make sure that your reasons for doing what you do are backed in facts and not assumptions.

If you assume that your targeting inputs are critical to the performance of your ads, you will likely prefer using Original Audiences in most cases. But, I encourage you to challenge that assumption. Experiment more thoroughly with Advantage+ Audience. Remember that your audiences are often expanded anyway when using Original Audiences.

Make sure that your reasoning for abandoning Advantage+ Audience is backed by a known weakness. If you primarily serve women, do not assume that if you optimize for purchases and use Advantage+ Audience that your ads will be shown to men. More than likely, it will be the opposite.

Your Turn

How do you approach when to use Advantage+ Audience or Original Audiences?

Let me know in the comments below!

The post Advantage+ Audience vs. Original Audiences appeared first on Jon Loomer Digital.

The Meta Ad Library was introduced in 2019 (then the Facebook Ad Library) in response to pressure faced by the company over misuse of advertising to manipulate elections. Eventually, the library would be expanded to cover transparency in the European Union and all other ads — though the level of detail varies.

The library itself is mostly buried, but there is plenty of useful information that can be found within it.

In this post, I’ll help you understand the following…

1. Meta Ad Library Basics: How to access and use it
2. Social Issues, Elections, and Politics
3. Ads Delivered to the European Union
4. All Other Ads
5. Branded Content
6. How You Can Use This Information

Let’s go…

Ad Library Basics

Go to https://www.facebook.com/ads/library/ to access the Meta Ad Library.

Within the Search Ads section, select a location, ad category (All Ads if it isn’t applicable), and a keyword.

You’ll then get a summary of all of the ads matching those search results.

You can refine your results by applying filters.

• Language: All or select specific languages
• Advertiser: All or select specific advertisers
• Platforms: All or select from Facebook, Instagram, Audience Network, and Messenger
• Media Type: All or select from images, memes, images and memes, videos, and no image or video
• Active Status: Active and inactive or select from one or the other
• Impressions by Date: Select a start and end date

You can find an individual advertiser’s ads by using the search. Another method is to go to the advertiser’s Facebook page (About > Page Transparency > See All > Go to Ad Library).

Social Issues, Elections, or Politics

When you search the Meta Ad Library, you have the option of filtering by Special Ad Category (Politics/Elections/Social Issues, Housing, Employment, or Credit).

If you select the category for Politics, Elections, and Social Issues, you’ll get additional details that can’t be found when viewing other ads (outside of the European Union, at least — we’ll get to that). These ads will be visible in the library for seven years.

Political ads allow for some additional filters for Delivery by Region, Disclaimer, and Estimated Audience Size when searching.

Search results for political ads will include the following details:

• Library ID
• Active or Inactive
• Started Running Date
• Platforms
• Categories
• Estimated Audience Size
• Amount Spent
• Impressions

Click “See Ad Details” for more. You’ll get the following…

1. About the Disclaimer: Disclaimers are required for political ads to declare who paid for them.

2. Ad Audience: The estimated audience size of those who saw the ad.

3. Ad Delivery: This includes the amount spent and number of impressions.

And also the age ranges, genders, and locations of those who saw the ad.

4. About the Advertiser: Additional details about the advertiser page in question, including the amount spent and disclaimers for other ads.

Ads Delivered to the European Union

Due to legal and regulatory requirements, an added layer of transparency is required for all ads displayed in the European Union. When you search for ads that have been delivered to any of these countries, you’ll get access to additional information.

Within the search results, you’ll get the following:

• Library ID
• Active or Inactive
• Started Running Date
• Platforms
• Whether there are multiple versions of the ad
• Number of ads that use the same creative and text

Click “See Summary Details” for more info. This will take you to a summary page with all of the related ads.

Click “See Ad Details” on any of the ads to get further breakdowns.

1. European Union Transparency: Location, age, and gender used in targeting (Facebook was targeting worldwide).

And the total number of people reached in the EU, broken down by country, gender, and age.

2. About the Advertiser: Basic details about the company running the ads.

3. Beneficiary and Payer: Ads that run in the European Union are required to disclose the beneficiary (the name of the business or individual benefitting from the ad) and payer (the business or individual paying for it). In many cases, it will be the same.

All Other Ads

For everyone else, you’ll get an overview of the active and inactive ads, but that’s pretty much it.

You can click “See ad details,” but there’s not a whole lot there.

You won’t get any of the details you found for political ads or those in the European Union related to the amount spent, estimated audience size, breakdown of the audience, and more. It’s mostly just the ad.

Branded Content

There’s also a link in the main navigation to Branded Content within the Meta Ad Library.

Branded Content isn’t “advertising” in the way the rest of these ads are set up. These are paid partnerships where one party creates content to promote another.

Select the platform (Facebook or Instagram), when that Branded Content appeared, and the name of the business or creator.

You’ll get a summary of the Branded Content that was published during that time period for the searched business or creator.

Click “See Post” to see it.

How You Can Use This Information

You’ll see a lot of advertisers talk about using this to “spy on the competition.” Sure. I guess you could do that. It’s not what I do. But, I see this as a far less intrusive tool.

The primary way that I use it is to see how a one-on-one client is currently using ads. When I prepare for a call, I may access their active ads by going to the Page Transparency section of their Facebook page. That helps me get a better sense of what they’re doing now before even getting on a call.

The second could be as inspiration. There are plenty of ad libraries out there used for this purpose (Meta has a separate library for creative inspiration), but you could run a search based on specific keywords related to your industry to see what others are doing.

Of course, you won’t get any details on how much was spent on those ads (outside of the European Union) or how they performed, but it would be asking quite a bit to get that type of info.

Your Turn

Do you use the Meta Ad Library? For what purpose?

Let me know in the comments below!

The post Meta Ad Library: A Detailed Guide appeared first on Jon Loomer Digital.

Should you use Instant Forms (often referred to as Facebook Lead Ads) or send people to a website form to build your email list? It’s a common question that I get from advertisers, and my answer has long been based on my own assumptions — or simply an instruction to “test it!”

I decided to take my own advice and stop making assumptions. I ran a test that generated 630 leads, and I’m ready to share what I learned.

The results were surprising — they were not at all consistent with my assumptions.

Hypothesis

My assumptions are sourced from years of advertising and an understanding of the balance of quality and quantity. I have assumptions based on two common options…

1. Instant Forms: The benefit of using Instant Forms is that they are much easier for the user. They load immediately and do not take them off of Facebook or Instagram. The form is pre-filled with information from their profile (unless a custom question is asked). But, for the same reason that Instant Forms can lead to more volume, you can expect lower quality.

2. Website Forms: It can be a little bit more difficult to complete these forms. The user is directed to an external website, which may be considered an unexpected interruption. If form questions remain the same, the completion of the form will take more manual effort. Combined with the less dependable variable of website performance, you might expect that the volume of leads from website forms will be lower and more costly, but the quality should be higher.

In summary, my hypothesis: Instant Forms will produce more leads at a lower cost, but website leads will be of a higher quality. I believe that the additional quality will override the negatives of less volume to make them more valuable and cost effective.

Defining Quality Leads

This is a step that seems elementary until we consider the variables, particularly related to volume, costs, and time.

Volume: We need enough volume for the results to be meaningful. If a very small percentage of the original leads is considered “quality” based on our definition, more raw leads are needed to complete the test. Ideally, I’m hoping to generate at least 100 quality leads to make this test meaningful.

For that to be possible, it’s not reasonable (for my funnel, at least) to define a quality lead as someone who makes a purchase. It needs to be a far more prevalent action.

Costs: This could also get out of hand if we insist on generating a high volume of very high quality leads in order to get meaningful results. I’m willing to spend $2k or so on this, but I’d rather not go beyond that.

Time: Defining quality can’t be concluded immediately upon collecting the lead. We need the leads themselves to define it by making an important action. That could be completed within a day or it may take weeks (or more).

I decided that the easiest way to balance these variables that is consistent with my own goals and funnel was to weed out the “dead leads.” These are people who aren’t reachable.

We could technically focus only on email deliverability, but I wanted to take it a step further. Something that is important to me is that my emails drive consistent traffic to my website. This is critical for three primary reasons:

1. Deep Engagement. By clicking links in my emails, this tells me that a lead is finding value in my content.

2. Website Traffic. This is an important factor for the growth of my business. I need people engaged on my website, sharing my content, and sending signals to search engines.

3. Potential to Buy. If you’re getting value from my website, you are much more likely to buy from me. That could mean setting up a one-on-one session, joining my private membership, or purchasing a course.

To make this decision even easier, I already track whether people click links in my emails as a way of segmenting my most engaged leads. I put tags on all important external links. When clicked, it sends users through a timed automation which gives them a Lead Score.

So, let’s summarize…

Quality Lead = Clicked a link in one of my emails.

The lead magnet in this test includes a series of educational emails that provide links for further reading. They may also receive other emails related to blog posts. These leads will have plenty of opportunities to open, click, or ignore my emails.

Time: Once the campaigns are complete, I will give the leads at least two weeks to click a link before declaring them “dead” (or dead until proven otherwise) — knowing that some of these leads may still “come back to life” at some point.

The Test

The vehicle for this test is a lead magnet for beginner advertisers. I actually tried to use other lead magnets, but this one provides the most volume for the lowest cost, which makes it the best candidate to generate adequate volume for a test. It also sends out several emails with links in them, which makes it a good candidate for measuring quality.

I created two different ad sets and ads that are identical in the following ways…

Targeting: Advantage+ Audience, offering suggestions of people who are in the top 25% of time spent on my website during the past 30 days and those who have performed the VideoWatched custom event (watched an embedded YouTube video on my website). Geography focused only on people in the United States, United Kingdom, Canada, and Australia.

I excluded all people who subscribed to what I was promoting via website custom audience, email custom audience, and lead form custom audience.

Placements: Advantage+ Placements.

Ad Copy and Creative: One ad with three different text variations (same for both versions). The only difference is that one drove people to a website landing page and one to an Instant Form.

Tagging and Segmentation: It’s critical that I keep these leads separate. All leads who came through the Instant Form were given a unique tag in my CRM. I created a separate landing page with a unique form for the website lead version and I gave people who were directed to this page and form a different tag. This allowed me to easily track the leads who came in from each source.

Tracking Quality: I alluded to this above, but I add a tag in my CRM to specific links in my emails. This includes important links from the eight-email sequence that came directly from this lead magnet. It also includes other emails I send from my newsletter and other broadcasts, since these people could subscribe to other offerings.

This tagging results in a Lead Score. If you never click a link, you won’t have a Lead Score. When you click, you’re sent through a timed automation. For the first seven days, you’ll have a Lead Score of 5. If you never click again, that score will drop from 4 on down to 1 as time passes. But it will never drop back to 0.

SIDE NOTE: I strongly encourage marketers to use a similar approach to segmenting your email list to isolate those who are most engaged. This has allowed me to implement a strategy to send more emails to those who are engaged, which increases the amount of traffic to my website while not driving up opt-outs.

Results: Costs

I generated a total of 630 leads from this test. I spent about $100 more on the website leads because the volume was lagging and I wanted it to get a bit closer to the leads generated from the Instant Forms.

Instant Forms: $801.26 spent for 392 leads ($2.04 per lead)
Website Leads: $897.78 spent for 238 leads ($3.77 per lead)

Ads Manager and my CRM didn’t match up perfectly (they were close), but my CRM is the ultimate source of generated leads. The number can’t be higher or lower than what my CRM says. I don’t care if some leads came in organically (very few did). And Ads Manager is the ultimate source for the amount spent.

In my original hypothesis, I expected that leads from Instant Forms may be less expensive. But, I’ve also seen that CPM costs can be higher with Instant Forms, so I was a bit surprised by how much cheaper these leads were. They were nearly half the cost.

Results: Quality

This is the most important part. Recall that I assumed that lead quality from Instant Forms would be lower due to the fact that they are easier to complete. While it was possible that overall Cost Per Quality Lead might even out, I still expected to get more quality leads from website forms.

Well, that was not the case…

Instant Forms: 114 of 392 leads were definitively “Quality” (29.1% and $7.03 per Quality Lead)
Website Leads: 69 of 238 leads were definitively “Quality” (29.0% and $13.01 per Quality Lead)

The percentage of definitively “Quality” leads is nearly identical for both Instant Forms and website forms. Note that these percentages will only increase with time, as more people could conceivably click on links in my emails. I was originally going to wait at least a month to write this post, but the changes were so small from week-to-week that any movement from here won’t be significant enough to alter my evaluation.

Of course, the percentage of quality leads isn’t the bottom line here. Instant Forms generated nearly twice as many leads (at nearly half the cost), which means that they produced quality leads at nearly half the cost of website forms.

I was certainly not expecting that.

Deliverability

I wasn’t planning on using this as a factor, but mentioning it above gave me the idea to run a check.

If I am unable to deliver an email to someone, there is no coming back from that “dead lead” designation. Lack of deliverability is typically due to either a bad email address (intentional or not) or an unsubscribe.

Is one method more prone to deliverability issues than the other?

Instant Forms: 328 of 392 leads were deliverable (83.7%)
Website Leads: 220 of 238 leads were deliverable (92.4%)

This is interesting, but not shocking. Something I learned during this process was that there were people subscribing from Instant Forms who were not getting my emails (they commented or messaged that they weren’t receiving them). The reason for this is that they were on my email list years ago and unsubscribed. If they don’t resubscribe from my CRM’s forms (which would be the issue with Instant Forms), it needs to be done manually.

In other words, the results from Instant Forms are even more startling. Despite having to overcome an additional 8.7% that weren’t deliverable, Instant Forms were still able to generate the same percentage of engaged (“quality”) leads.

Learnings and Potential Adjustments

It’s difficult to argue with these results. There is enough volume to learn something from them. At the very least, it’s evidence that Instant Forms may be just as effective as website forms at generating quality leads.

Beyond that, I was a bit disappointed in the overall percentage of quality leads. Obviously, this applies to both the Instant Forms and website forms, since those percentages were about the same.

But, that’s something that has a long list of potential explanations. These are things that I can tweak…

1. The Lead Magnet. One of the reasons I didn’t love the idea of using the Beginners product as my lead magnet is that I don’t think these people align with my content all that well. They’re good to get in the door. But, this lead magnet served the purpose of generating more volume. I may have been able to use a different lead magnet to generate higher quality leads overall, but the costs may have been twice as high.

So, I still think this was the right choice for the test. But, going forward, it’s worth trying other lead magnets that better align with my more advanced content.

2. Targeting. I can’t say that this was a mistake, but only that it’s a potential factor. I firmly contend that you should use Advantage+ Audience for sales, but you should avoid it for the top of the funnel. Middle of the funnel is where it gets a bit hazy. There’s the potential for quality to be a problem.

What’s nice about Advantage+ Audience is that the suggestions you make shouldn’t be all that impactful, which limits the variance in results depending on what you use for inputs.

That becomes far more variable when using original audiences. It’s possible I could get better results on a smaller scale using interests or custom audiences or maybe even lookalike audiences. But those results will likely fall off eventually.

I could potentially use these same custom audiences with Advantage Custom Audience, but I suspect the results would be mostly the same. It still could be worth testing.

Increasing Quality

It’s also important to point out that there are endless ways to increase the quality of your leads. The fact that I’m at a shade under 30% is absolutely correctable. Beyond the type of lead magnet and targeting, there are some other rather obvious solutions…

1. More Questions. Whether it’s an Instant Form or website form, there’s a clear correlation between quality and quantity. If you want more volume, ask fewer questions. If you want higher quality leads, ask more questions.

2. Custom Questions. This is particularly the case for Instant Forms, that pre-fill answers for basic information that can be pulled from a lead’s profile. I can ask custom questions that require people to put thought into their answers.

3. Conversion Leads Optimization. This is something I’ve been setting up for the past few months, and I’ll be able to optimize for very soon. When running ads to Instant Forms, you have the ability to optimize for Leads or Conversion Leads.

To get anything out of Conversion Leads, you first need to go through a multi-month setup process to help Meta understand your CRM funnel. I’ve been doing that using leads from Instant Forms and sending events when people click my links. The process is 95% complete, so I hope to begin optimizing for Conversion Leads soon.

In all of these cases, it will be more expensive to get the lead. This is part of that balance we keep discussing. We already know that Quality Leads cost me between $7 and $13. Will Conversion Leads help decrease that cost? We won’t know until we try it.

Test Your Assumptions

This was a fun test, and I encourage you to always test your assumptions like this. Especially if you’ve been doing this for a long time, it’s easy to fall into complacency where you just assume that, through all of the changes of Meta’s products and systems, everything will work the way it always has.

It doesn’t mean that my test definitively proves that Instant Forms generate more quality leads at a lower cost than website leads. Far too many factors contribute to that determination to make such a statement.

But, my results were certainly eye-opening enough for me to take a step back and reassess what I previously believed to be true.

Your Turn

What kinds of results have you seen from Instant Forms vs. website forms?

Let me know in the comments below!

The post Results: Testing Quality Leads from Instant Forms vs. Website appeared first on Jon Loomer Digital.

Dynamic Creative was discontinued for Sales and App Promotion objectives in June of 2024. Meta recommends using Flexible Ad Format in those cases instead. Read about the details of this update here.

Dynamic Creative was first rolled out in 2017. And yet, you can make an argument that it’s a feature that has never been more relevant.

The landscape has changed. Best practices are evolving. While testing in years past often focused on differences in the ad set, it’s now shifted almost entirely to the ad.

There are four primary ways to test ad creative:

1. Run multiple ads
2. Use the Text Variations feature
3. Dynamic Creative
4. A/B Test

The focus of this post, of course, is on Dynamic Creative: How it works, how to use it, best practices, and viewing results.

How it Works

When you create a campaign, there may be several approaches that you want to try when it comes to creative. Different images, videos, and text. You could create separate ads to test out these variations. Or you can use Dynamic Creative.

Dynamic Creative allows you to submit multiple images or videos, primary text, headlines, descriptions, and call-to-action buttons for a single ad. Meta will then mix and match to show variations based on different combinations in an effort to get you better results.

You can submit the following creative variations:

• Images or videos (or a combination): Up to 10 total
• Primary text: Up to 5
• Headlines: Up to 5
• Descriptions: Up to 5
• CTA Buttons: Up to 5

These variations won’t be shown equally and it’s not a true split test, but it’s a scalable approach to creative variations. Instead of creating 10 or 20 ads (that may or may not get shown) based on specific copy and creative variations, submit up to 30 creative assets and let Meta find what works.

You’re unlikely to reach it, but know that you can create a maximum of 1,000 Dynamic Creative ads.

How to Set Up

Dynamic Creative is available using any campaign objective. Within the ad set, toggle Dynamic Creative on.

When you do, you may get this message…

Now, create your ad. As noted in the message above, Catalog ads will be deactivated. Select single image or video or carousel as the ad format.

Add up to 10 images or videos, or a combination thereof.

If you use the carousel format, you can only include up to 10 images.

The ability to submit up to five primary text, headlines, and descriptions was originally a Dynamic Creative-only option. It’s now available for all ads.

And finally, add up to five CTA button options.

Optimize Creative for Each Person

Optimize Creative for Each Person was originally unique to Dynamic Creative, but you can also find it when running Traffic campaigns without Dynamic Creative.

When using Dynamic Creative, it’s on by default but can be turned off.

Enhancements include optimizations like cropping, applying a template, swapping text between fields, creating videos from your images, and more. Most, if not all, of these optimizations have been absorbed into Advantage+ Creative.

Instead of having the option of turning on Advantage+ Creative when you run Dynamic Creative ads, you can turn on Optimize Creative for Each Person.

Best Practices

When does using Dynamic Creative make the most sense, and how can you get the most out of it? Here are a few thoughts…

1. One ad versus multiple defined ads. You have lots of creative and text possibilities, but you don’t have a preferred approach. Instead of throwing multiple ads into the rotation, combine copy and creative and allow the algorithm to sort it out automatically.

2. You don’t care about finding a “winner.” This isn’t a split test, and you won’t find results that tell you which combination is the top performer. But, you’re okay with that.

3. Make sure the assets will work together. Keep in mind that each image and video needs to work with each primary option that you provide. Don’t craft text that refers to your video if you may also have images. It may be best to keep copy short and simple.

4. You don’t need to submit the maximum number of options. Just because you can submit 10 images or videos doesn’t mean you should, just as you don’t need five primary text options, headlines, descriptions, and CTA buttons. If you have a large budget, feel free to take advantage of it. Otherwise, limit what you submit to your best text and creative options.

Segment Your Results

Dynamic Creative isn’t for everyone, especially if you demand full control and transparency. You won’t be able to determine how text and creative are combined. If you want that, just create ads the way you want them. And you won’t see a detailed itemization of results by creative combination.

But, there are a couple of things that you can do…

First, you have access to a Breakdown feature for Dynamic Creative. While in the Ads tab, click the Breakdown drop-down menu and select “By Dynamic Creative Element.” You’ll then get access to breakdowns by creative, text, headline, description, or CTA button.

You won’t get results by combination of these elements, but you can get a breakdown by each element. Here’s an example for primary text…

While you can’t get results by creative combinations, you are able to manually view the top performing combinations by engagement.

You can access this information by using the instructions below…

Your Turn

Do you use Dynamic Creative? What results do you see?

Let me know in the comments below!

The post A Guide to Dynamic Creative in Meta Ads Manager appeared first on Jon Loomer Digital.

Creative testing with Meta advertising is an inexact science. It seems every advertiser has their own approach. Some will swear it’s the “right way,” but the best option for you is more nuanced.

It depends on the situation, what you care about, and what you’re trying to accomplish.

In this post, we’ll cover four ways to approach creative testing:

1. Create Multiple Ads in an Ad Set
2. Use Text Variations
3. Use Dynamic Creative
4. Run an A/B Test

By the end, we’ll discuss what I do and how to determine what’s best for you.

1. Create Multiple Ads in an Ad Set

There’s nothing wrong with kicking it old school and simply creating multiple ads for a given ad set with different combinations of copy and creative. But, there are some basics to consider when doing this.

Ads won’t be shown equally, if at all.

If you’re a control freak, this will drive you crazy. Just because you created four ads doesn’t mean that Meta’s ad delivery algorithm will show them equally to help you understand what works best. In fact, one or more of the ads may not show at all.

There has to be a certain amount of letting go of control with this approach. You need to be okay with the fact that you might create an ad that doesn’t get shown. Or maybe your favorite ad won’t get shown the most.

Trust the algorithm, but understand its imperfections.

When you take this approach, you embrace the chaos and imperfection of it from the outset. Your ads won’t be shown equally and some may not be shown at all. You are trusting that the algorithm will use historical and real-time data to help deliver the right versions to the right people.

But the algorithm will also make these decisions very quickly because, in most cases, any differences in ad performance won’t be statistically significant.

This isn’t a true split test.

If you have multiple ads in an ad set, it’s not a true A/B split test. The same user can see more than one version of your ads. In many cases, this is preferred anyway. But, that overlap means that you’re not going to see results based on a true, scientific split test.

And you need to be okay with that.

Consider a limit of six ads.

Assuming you aren’t running an Advantage+ Shopping Campaign, Meta recommends using no more than six ads in an ad set. Once you’ve added more than six, there’s marginal benefit.

Create the ads at initial publication, if possible.

Every time you publish a new ad, you’ll restart the learning phase. Not every advertiser sees this as a big deal, and there are times when it definitely doesn’t matter. But, it’s typically best to create all of your ads at the start, rather than doing it later on and having to roll the dice on messing with results.

2. Use Text Variations

This feature has also been named Multiple Text Options or Multiple Text Optimization in the past. No matter what you call it, the functionality is the same.

When assembling your ad, you can create up to five variations of your primary text, headline, and description.

This is a great way to create variations while using only one ad. Meta will show combinations of text to people based on what they’re more likely to respond to. That could be due to what other people respond to, what the individual user has responded to in the past, the placement, and more.

Meta also generates primary text options that you can choose from using AI.

I’ve found these rarely match up with my voice, so I don’t use them. But, it’s something worth testing out.

If you require control, you will not like this feature. There is no way of dictating how much a text variation is used — or whether it’s used at all. And since all of the variations contribute to the same ad, you won’t be able to see which combination led to the best results.

What you can do, though, is use the Breakdown by Dynamic Creative Element.

A separate row will be generated for each variation, but you won’t see which combination performed the best.

Today’s advertiser needs to be okay with not always being in control while putting a certain amount of trust in the algorithm. This is a feature I regularly use, and I’m not overly concerned about “finding a winner.” Instead, I use it knowing that if I give the algorithm more options, I give it more opportunities to get the best possible results.

3. Use Dynamic Creative

Dynamic Creative was discontinued in June of 2024. Meta recommends using Flexible Ad Format instead. Read about the details of this update here.

Dynamic Creative is not a new feature (I first wrote about it in 2017), but it’s still useful.

Dynamic Creative combines multiple images, videos, and other ad components (primary text, description, headline, and CTA button) to find the best possible results while creating only one ad. This is similar to the Text Variations option, but it also includes creative and CTA buttons.

This feature is turned on in the ad set.

When using “Single Image or Video,” you can upload a combination of up to 10 images and videos. It could be all images, all videos, or a combination thereof.

You have the option of turning on Optimize Creative for Each Person. When this is on, ad creative and destinations vary depending on what an individual person may respond to.

You can also test various CTA button options.

Like every option so far, this is not a true split test. If you’re hoping to test specific options against one another, this is not the option you want to use. Dynamic Creative is best for situations where you have several creative options, but you’re willing to give up control to the ad delivery algorithm.

As is the case with Text Variations, you will not see which combination of creative, text, and CTA button performs best. But, you can use Breakdowns to see how each individual item performed.

4. Run an A/B Test

A true A/B test is ideal for the control freak who has something very specific that needs to be tested. You want to find the best performer between two or more ads, free of overlap.

While you can run the options above indefinitely, an A/B test is meant to be temporary. You find a winner so that you can leverage it and turn off the losing variation. That’s why you’ll also need the benefit of time to run an A/B test.

Finally, keep in mind that your results are unlikely to be ideal during an A/B test. Your ads won’t be distributed optimally during this test because the entire goal is to segment your audience so that one half sees one version while the other half sees the other.

If you want to create a variation of an existing ad to test against the original, select the existing ad and click “Duplicate.” Then select “New A/B Test.”

For the variable that you want to test, select “Creative.” Then select the ad that you want to copy.

Pick the key metric that will determine a winner.

Then set a start and end date for the test. You can choose to have the test end early if a winner is found before the end date.

Unlike the other options listed in this post, an A/B test will give you a true winner — assuming that a winner is found and is statistically significant.

Which is Best for You?

The option that you choose for testing creative depends on your situation and what is important to you.

If you desire control and certainty and want to determine which ad is the top performer, use the A/B test option.

Otherwise, you’ll run a combination of the other three options. I rarely have a deep desire to know which ad is the top performer with an A/B test. It suggests that I already found two ads with preferred combinations of text and creative. And that is almost never the case.

When I create an ad set, I typically use multiple ads. Each ad will utilize a different format (video, image, or carousel), or maybe a different version of one of those formats. And each ad utilizes Text Variations.

Admittedly, I haven’t used Dynamic Creative for several years. But, I have heard that some advertisers still swear by it, and it’s not all that different from using the Text Variations optimization.

Like everything else, know your needs and style. Do what works for you.

Your Turn

Which approach do you take to creative testing?

Let me know in the comments below!

The post 4 Ways to Approach Creative Testing with Meta Advertising appeared first on Jon Loomer Digital.

Today’s post is a bit on the experimental and hypothetical side. But it’s inspired by a very real problem that I see Meta advertisers make that can be fixed with a restructuring of the current campaign construction flow.

Redesigning the campaign flow is nothing new for Meta. It happens every few years, and it’s necessary. Meta is in a continual state of change, adding and tweaking features. This means that the feature set is different today than when things were last reorganized. That creates clutter.

And we have a whole lot of clutter. That clutter creates confusion.

The last time Meta redesigned campaign construction flow, it was with ODAX (Outcome-Driven Ad Experiences). The purpose was to simplify and consolidate campaign objectives, moving from 11 to six.

I don’t know that a drastic redesign is required of objectives. I will recommend trimming to five, but that’s not the biggest issue here.

The Problem with Performance Goals

The primary source of clutter comes from performance goals. It’s also what creates confusion.

The primary purpose of selecting a campaign objective is to declare what it is you are trying to accomplish. Which of these six things is your focus?

• Awareness
• Traffic
• Engagement
• Leads
• App Promotion
• Sales

Meta then streamlines the rest of the campaign creation process by removing certain options within the ad set. Your campaign objective helps determine which conversion locations and performance goals are available, for example.

It would be logical to assume that all of the performance goals are related to that objective, but it’s just not the case. When you select the Sales objective, you have several performance goal options which have nothing to do with fulfilling the task of sales.

“Number of Conversions” and “Value of Conversions” are the only performance goals that will help you drive more sales. The others (Landing Page Views, Link Clicks, Daily Unique Reach, and Impressions) are unlikely to lead you there.

That doesn’t mean there’s no reason to use those other performance goals. They’re simply not directly tied to Sales and shouldn’t be included within the Sales objective.

This is what creates so much confusion. Advertisers believe that there’s some sort of sales-related optimization power happening because they select the Sales objective, but that’s not necessarily the case.

If you select Impressions, your ad’s just going to get shown a bunch. That’s it. If sales happen, it’s incidental and not a focus of the delivery algorithm.

There are 21 performance goals in all and 71 different combinations of ways to get to them. That needs to be simplified.

Below is my proposal for how the new campaign objectives could be structured with the conversion locations and performance goals beneath them…

1. Awareness

This is the one objective that needs the least amount of tweaking, but it’s already the simplest.

There aren’t currently any conversion location selections. I’m sure you could technically add a layer here with conversion locations, but I don’t know that they really matter.

Proposed Performance Goals:

• Reach
• Impressions
• Ad Recall Lift
• NEW: Daily unique reach

All of these performance goals are related to Awareness in some way or another. I’m not sure why Daily Unique Reach wasn’t already an option, but I’m adding it.

Performance Goals Removed:

• ThruPlay Views (moved to Engagement)
• 2-Second Continuous Video Views (moved to Engagement)

These video view goals seem out of place for Awareness. It’s not that video videos don’t impact awareness. But, these should be part of engagement.

2. Engagement

This was already the fullest objective, prior to this process. Since I’m removing the Traffic objective (more on that later), any related performance goals were moved here.

Proposed Conversion Locations:

• Messaging apps
• On your ad
• Calls
• Website
• Facebook page
• Facebook group
• NEW: Instagram profile

It may seem like overkill, but all of these are needed for various engagement goals where the advertiser wants link clicks, landing page views, messaging conversations, video engagement, or post engagement.

The Instagram Profile conversion location was previously included under Traffic for ads driving to your Instagram profile, and that seems like a better fit here.

Conversion Locations Removed:

• App (moved to App Promotion)

There’s an objective for App Promotion which should cover any promotion of your app, as the name implies.

There are a whole lot of performance goals here, I’ll admit. But, unless you were to split off a new objective for Messaging or Calls, these all seem to make sense here.

Also keep in mind that these performance goals don’t all appear in one drop-down menu. It depends on which conversion location is selected.

Proposed Performance Goals:

• Click to Message
• Sponsored Message
• ThruPlay Views
• 2-second continuous video views
• Engagement with a post
• Event responses
• Reminders set
• Calls
• Website conversions (non-purchase and non-lead)
• Landing page views
• Link clicks
• Page likes
• NEW: Conversations
• NEW: Instagram profile visits

The Conversations performance goal is currently included within the Sales objective under the Messaging Apps conversion location. While you may want Sales from that engagement, it’s not the optimized action.

Performance Goals Removed:

• Daily unique reach (moved to Awareness)
• Impressions (moved to Awareness)
• App events (moved to App Promotion)

Daily unique reach and Impressions will appear repeatedly. I’m not sure why Meta insists on making them so readily available, regardless of objective.

3. Leads

This objective should be the most straightforward, but you’ll see that Meta currently clutters it up with completely unnecessary options.

Only keep performance goals that actually allow you to optimize for Leads.

Proposed Conversion Locations:

• Website
• Instant forms
• Messenger
• Instant forms and Messenger
• Instagram

Conversion Locations Removed:

• Calls (moved to Engagement)
• App (moved to App Promotion)

Sure, phone calls could technically be used to drive leads. But that’s incredibly difficult to measure and there’s no optimization for the lead itself from a phone call. Just use Engagement and the Call conversion location.

Once again, let’s move all app-related optimization to App Promotion.

Proposed Performance Goals:

• Website Conversions (Lead and Complete Registration only)
• Leads
• Conversion Leads

Super simple. You want leads? Set a performance goal related to leads.

There is no reason to include any of the following performance goals for the Leads objective. If you’re using any of these, do not expect to generate leads. Find a different objective.

Performance Goals Removed:

• Landing page views (moved to Engagement)
• Link clicks (moved to Engagement)
• Daily unique reach (moved to Awareness)
• Impressions (moved to Awareness)
• Calls (moved to Engagement)
• App events (moved to App Promotion)

4. App Promotion

The only conversion location for App Promotion is your app, so this is rather simple. You could technically add the Website and App conversion location here, but let’s keep that simple and leave it with the Sales objective.

Proposed Performance Goals:

• App events
• App installs
• Value of conversions
• NEW: Link clicks

I like how clean it is to keep one performance goal in a single objective, but I needed to make an exception with link clicks here because we’re talking about app promotion. You should still be able to optimize for link clicks, but that action is moved here.

Performance Goals Removed: NONE

The one potential problem will be Awareness-related performance goals to promote your app. I’m not sure how often advertisers do that now. If Meta can’t add App as a conversion location for the Awareness objective, we may need to add the awareness-related performance goals here.

5. Sales

This may be the objective that is used most often and which leads to the most misunderstandings. It’s too complicated now. Everything we do here should be related to driving sales.

Proposed Conversion Locations:

• Website
• Website and App

This got a little tricky. I want to continue to move anything app-related to App Promotion. Unfortunately, there’s a Website and App conversion location, so it needs to go somewhere. It could technically go either here or within App Promotion.

Conversion Locations Removed:

• App (moved to App Promotion)
• Messaging Apps (moved to Engagement)
• Calls (moved to Engagement)

You can generate sales with your app, too, but use App Promotion for that. Same goes for Messaging Apps and Calls, but there’s currently no way to optimize for the purchase when using those locations. If that changes, we can add them back.

Proposed Performance Goals:

• Conversions (value-based only)
• Value of conversions

It’s simple. Use the Sales objective to optimize for value-based conversion events. Otherwise, find a different objective.

That means, there’s a whole lot of stuff that will be moved out of this objective…

Performance Goals Removed:

• Landing page views (moved to Engagement)
• Link clicks (moved to Engagement)
• Daily unique reach
• Impressions (moved to Awareness)
• App events (moved to Awareness)
• Conversations (moved to Engagement)
• Calls (moved to Engagement)

REMOVED: Traffic Objective

This objective has no unique purpose. It’s primarily a way to send link clicks and landing page views to your website, app, messaging apps, and Instagram profile (as well as optimize for calls). All of this could be done within Engagement. Link clicks and landing page views are, after all, a form of basic engagement.

So, to make it official…

Proposed Conversion Locations: NONE

Conversion Locations Removed:

• Website (moved to Engagement)
• App (moved to App Promotion)
• Messaging apps (moved to Engagement)
• Instagram profile (moved to Engagement)
• Calls (moved to Engagement)

Proposed Performance Goals: NONE

Performance Goals Removed:

• Landing page views (moved to Engagement)
• Link clicks (moved to Engagement)
• Daily unique reach (moved to Awareness)
• Conversations (moved to Engagement)
• Impressions (moved to Awareness)
• Instagram profile visits (moved to Engagement)
• Calls (moved to Engagement)

Meta could make Traffic worthwhile if they ever create performance goals that are unique to website traffic — specifically quality traffic actions and behavior. Until that happens, it’s a mostly pointless objective.

Your Turn

This is my vision for what a new simplified version of the campaign objective flow could look like. It’s not perfect, and I’m sure there are holes. But anything you’d change or add?

Let me know in the comments below!

The post How Meta Could Improve Campaign Construction Flow appeared first on Jon Loomer Digital.

Meta Ads Manager and Ads Reporting provide access to countless standard metrics. But there are times when the metric you need isn’t available, and a custom metric can be created using a formula that combines existing metrics.

In this post, let’s get you started with creating your own custom metrics…

Access Custom Metrics

Custom metrics can be used in either Ads Manager or Ads Reporting.

Within Ads Manager, click Customize Columns from the Columns dropdown menu.

If you’ve ever created custom metrics before, they will appear at the top. Otherwise, click the link next to the search bar to create a custom metric.

You’ll then see the following…

We’ll get to this in a moment. You can also access this from Ads Reporting.

From the pivot table on the right, select the Metrics tab. Scroll down to Custom Metrics, and you can click the button to create one.

The process of creating a custom metric will look the same, regardless of whether you’re in Ads Manager or Ads Reporting. The metrics that you create can be used from either location.

Create a Custom Metric

Now let’s create that custom metric.

This process uses formulas. All you need is some basic math knowledge to create a custom metric.

It could be as simple as Metric 1 + Metric 2 or a much more complicated mathematical formula like ((Metric 1 + Metric 2)/5)*Metric 3. Custom metric possibilities are limited by your own math skills and the metrics available.

To build your formula, you can simply type it out directly in the text field. When you start typing the name of a metric, the autocomplete will come up for you to select it.

You can also use the Select Metric drop-down menu to find what you want to use.

There are popular metrics at the top, followed by metrics grouped by category. As an example, here’s what you see for Performance.

In addition to Meta’s standard metrics, you can use standard events, custom events, and custom conversions.

After you create your formula, you’ll need to name the metric…

Select a format (don’t forget this!)…

Include an optional description…

And then determine who can use it. Options are only you or everyone who has access to the business.

Try Popular Formulas

On the right hand side, Meta includes several very basic formulas that you can use.

When you click any of these, the formula is automatically added to the text field. Here are examples…

Impressions to 3-second video plays rate

What percentage of impressions results in at least a 3-second video play?

Impressions to post engagements rate

What percentage of impressions results in some sort of engagement?

Link clicks to landing page views rate

What percentage of link clicks results in a loaded landing page?

Video plays to link clicks rate

What percentage of video views results in people clicking links?

Link clicks to purchases rate

What percentage of link clicks turns into purchases? This is one way to measure Conversion Rate.

Other Examples

I have a collection of custom metrics that I use that range from the very basic to super complicated.

50% Scroll vs. Landing Page View

What percentage of landing page views results in a 50% scroll of the page? This requires a custom event.

Cost Per Video Plays at 95%

Amazingly, this metric doesn’t otherwise exist.

Website Engagement Score

This one is a bit over the top, but it attempts to weight the value of certain actions on my website (mostly custom events).

There are several more, but most are only valuable for me because of the custom events that I use.

The need for custom metrics can come from the fact that a basic metric just doesn’t exist (like the Cost Per Video Plays at 95% metric). Or it could be something that’s much more customized to your own needs.

Formula Errors

The biggest issue I’ve had with custom metrics is that custom events can break the formulas. But, I believe I understand why — it’s due to the way that I name custom events.

Notice that all of my custom events that are multiple words and numbers include spaces in them.

This isn’t unique to custom events since you’ll see the same thing with standard events and other basic metrics.

If I try to create a formula based on a custom event that includes spaces in the name, I’ve seen one of two things happen. Either it breaks into multiple metrics or it looks like this…

In either case, the metric doesn’t calculate.

But, if I use a custom event without a space, it works as it should…

As I said, this bug is unique to custom events. If I use standard events (on the left) or even custom conversions (on the right) that have spaces, they work fine.

So, this bug is indeed unique to custom events. It’s also entirely possible that this isn’t a bug that impacts everyone, but it’s always been an issue for me.

There are two potential solutions:

1. Create a custom conversion mapped to the custom event
2. Stop adding spaces in your custom event names

Of course, the second option is fine going forward, but the first fixes events that you already have.

Meta also lists out several other potential formula errors that, frankly, I’ve never run into before. Some are basic math errors (dividing by zero), but I either don’t fully understand some of these errors or I just haven’t run into them. But, maybe you have…

1. You need at least two metrics and one symbol in a formula.
2. You need to ensure that all formulas follow a mathematical order from left to right, starting with brackets, order of powers or roots, division,
3. multiplication, addition and subtraction.
4. You cannot place two opening parentheses (( and two closing parentheses )) next to each other.
5. You cannot use the parenthesis symbol after a number or another parenthesis.
6. You cannot use the parenthesis symbol after another symbol.
7. You cannot use another metric or closing parenthesis ) before a metric.
8. You cannot place two symbols right next to each other.
9. You cannot divide by zero.

Should You Use Custom Metrics?

I feel like the custom metrics feature is one that mostly goes unused, but that’s primarily because the typical advertiser doesn’t know that they exist. They may not be the secret to amazing ad performance, but they can simplify the interpretation of results.

You can get away with never using a custom metric. But, there’s also something kind of cool about creating metrics that you may be the only one who uses. You can create metrics that are unique to the things that you care about and measure performance.

Okay, look. I may just judge you if you never create a custom metric. Typically, it means that you care just a little bit more about measuring what’s important.

Your Turn

Do you use custom metrics? What are examples of some that you’ve created?

Let me know in the comments below!

The post A Guide to Custom Metrics in Meta Ads Manager appeared first on Jon Loomer Digital.

My goal is to build the most thorough, comprehensive, and helpful resource for Meta advertisers. While I believe I’ve done that during the past 13 years, one problem is surfacing all of the most helpful content.

Yes, it’s all helpful. But, I’ve created so many guides during the past year alone that are cornerstone articles for any Meta advertiser that it may be difficult to sift through. I want to aggregate all of that content into one place.

This isn’t all beginner content. It’s beginner, intermediate, advanced, and even more advanced.

The title of this post is misleading. While there are 16 cornerstone Meta advertising topics included below, there are a total of 27 guides in all. Most of it was written during the past year, but all of it is relevant and current as of today’s publication date.

No, you won’t be able to read all of this in one sitting. But you should peruse what you need right now and save the rest for later. You will need it.

1. The Auction

Do you understand how the Meta ad auction works? Maybe you know that it involves bids and ad scores. But if you’re like most advertisers, the explanation gets fuzzy from there.

Let’s clear up the confusion…

READ: How the Facebook Ad Auction Works

2. Advantage+ Shopping Campaigns

If you run ads for an e-commerce brand, you absolutely must experiment with Advantage+ Shopping Campaigns. And even if you don’t, you should consider it. This is Meta’s most advanced machine learning driving a single campaign type.

Once you understand Advantage+ Shopping Campaigns, you will have a much better understanding of where Meta advertising is headed.

READ: Get Started with Advantage+ Shopping Campaigns

3. Campaign Objectives

You have six options, so you’d think this is simple. But so many advertisers mess this up. They completely misunderstand what the campaign objective actually does — and doesn’t do.

Don’t let that be you…

READ: Meta Campaign Objectives: Best Practices

4. Special Ad Categories

If you promote anything related to credit, employment, housing, politics or social issues, you need to declare a special ad category. That will impact the options available to you.

READ: Special Ad Categories: A Guide for Meta Ads

5. Advantage Campaign Budget

Should you set your budget at the ad set level or use Advantage Campaign Budget and allow Meta to distribute optimally between ad sets — assuming you use multiple ad sets?

READ: Advantage Campaign Budget Best Practices

6. Performance Goals and Ads Optimization

Now that targeting inputs matter less in the current stage of Meta advertising, the Performance Goal is now the most important. In fact, I’d say it replaces targeting as your way to determine who sees your ads.

Understand how optimization for ad delivery works, which performance goals you should select, and the mistakes you must avoid…

READ:

• A Guide to Meta Ads Optimization for Delivery
• 21 Performance Goals: The Focus of Meta Ads Optimization
• Common Ad Set Optimization Mistakes Advertisers Make

7. Attribution

Attribution is how Meta gives credit to an ad in your reporting. But it’s so much more than that. The Attribution Setting impacts optimization and reporting, and knowing how to properly decipher your results is critical.

So many mistakes start with attribution…

READ:

• Meta Ads Attribution Setting: A Complete Guide
• 5 Most Common Attribution Mistakes Advertisers Make
• Compare Attribution Settings: Get the Most of Meta Conversion Data

8. Conversion Events

Proper attribution is heavily reliant on your standard events, custom events, and custom conversions. Do you know the differences between them and how they are used? Do you know how to set them up and test them?

This is so important…

READ:

• A Guide to Standard Events, Custom Events, and Custom Conversions
• How to Test Meta Conversion Events
• Meta Conversion Events, Deduplication, and Conflicting Reporting

9. Bid Strategies

You may not even know that bidding happens with all campaigns. By default, you will typically use the Highest Volume bid strategy. But there are several others that you could use — but only certain times when you should use them.

Start here with bidding…

READ: Bid Strategies Best Practices for Meta Advertising

10. Targeting

Targeting is where Meta advertising has changed the most during the past few years. It’s also where advertisers remain stubborn, resisting change. They make countless mistakes in this area.

Do you?

READ:

• The Ultimate Guide to Meta Ads Targeting
• Advantage+ Audience Best Practices Guide
• When Broad Targeting Fails
• The Evolution of Who Sees Your Ads

11. Budget

Your budget impacts results far more than advertisers like to admit. What’s an appropriate starting budget? How do you determine your budget? How do you get results without breaking the bank?

Let’s try to answer those questions…

READ:

• How to Determine Your Facebook Ads Budget
• Facebook Ads on a Budget

12. Placements

There was a time when it made sense to manually change placements in nearly all cases. Those days are in the past. But, there absolutely are times when you should use Advantage+ Placements and times when you shouldn’t.

Do you know when it makes sense to remove placements?

READ:

• A Guide to Meta Ad Placements
• Common Advertising Mistakes Related to Placement Selection

13. Breakdowns

Breakdowns may be the most awesome and underutilized advertising feature. You can uncover absolute gold with just a couple of clicks.

If you aren’t using breakdowns now, it’s time to start…

READ: A Guide to Breakdowns in Meta Ads Manager

14. Automated Rules

Automated Rules are a great way to automate what are otherwise manual processes to increase efficiency and improve performance. Use Automated Rules to automatically increase your budget based on performance. Or create rules to manage Audience Fragmentation or Auction Overlap.

READ: A Guide to Automated Rules

15. Split Tests

A/B Tests are the one way to create a truly scientific split test without overlapping audiences to find what works best. Do you use them? Do you know how?

READ: How to Create an A/B Test in Meta Experiments

16. Spending Limits

There are some spending limits that you may apply yourself. There’s another that Meta may enforce without you knowing. Regardless, these could be causing you problems.

READ: Campaign Spending Limits, Account Spending Limits, and Daily Spending Limits

BONUS GUIDES

Okay, there are more than 16 topics and 27 guides. I’ll try to add new guides as I create them.

READ: A Guide to Custom Metrics in Meta Ads Manager

Your Turn

Okay, after all of this… What guides are missing?

Let me know in the comments below!

The post 16 Cornerstone Meta Advertising Guides appeared first on Jon Loomer Digital.

Automated Rules allow you to save time and increase efficiency by automating changes to your campaigns, ad sets, and ads when specific conditions have been met. In this post, you’ll learn how to access and set up these rules to enhance ad performance.

To access Automated Rules, use the All Tools menu in Ads Manager and you’ll find it within the Advertise group.

Click to create a rule at the top left…

A Note on Rules Templates

Originally, advertisers were provided multiple options for templates that they could choose from when creating an Automated Rule.

Templates covered ways to automatically control Advantage+ Creative, Auction Overlap, and Audience Fragmentation. This is no longer the case.

Truthfully, these rules always felt out of place. They didn’t trigger based on performance or any metric. This is the entire purpose of the custom rules. That said, these are still available — they just aren’t part of Automated Rules.

Items within these templates can now be found within Automatic Adjustments on your Account Overview page.

Custom Rule

Now when you click to create an Automated Rule, you’ll be taken through the custom rule creation process.

Custom rules are for when you want to automate changes that you typically make manually based on performance. You may turn an ad set off or lower budget based on a high Cost Per Action. You could increase the budget of a high-performing ad set. Or you might increase or decrease manual bids. Since you can have these actions run in the background automatically, it can improve your efficiency.

First, decide whether you want this rule to apply to all active campaigns, ad sets, or ads.

If you want to limit the execution of this rule to specific campaigns, ad sets, or ads, see the end of this post.

Next, select the action that you want this rule to execute. You have the following options, depending on whether rules apply to campaigns, ad sets, or ads:

Campaigns: Turn off/on, send notification, or adjust budget.

Ad Sets: Turn off/on, send notification, adjust budget, or adjust bid.

Ads: Turn off/on or send notification.

Set the conditions when your rule would apply.

Define a time range to determine the amount of data to base your rule on. For example, you may want to increase budget by 10% if Cost Per Conversion is under $10 for 7 days.

Determine how frequently the rule will run. This is different from the time range, which determines the amount of data the rule is based on. You could have a rule run once per day that is based on the prior 7 days of data.

And finally, determine how you’d like to be notified.

Here’s an example of what a rule could look like to increase the budget 10% if Cost Per Purchase is under $20, pulling from three days of data and checking on a daily basis…

Apply to Specific Campaigns, Ad Sets, or Ads

When you create rules from the Automated Rules section, they will apply to all active campaigns, ad sets, or ads. But, you can create or apply rules to specific advertising, too.

From the Ads Manager table view, check the box of a campaign or ad set that you want a rule to apply to. Then click the Rules dropdown menu and select from the following options:

• Create a New Rule
• Apply an Existing Rule
• View Active Rules
• Manage Rules

If you create a new custom rule, you’ll see that you have the option of applying this rule to advertising you selected or all that is active.

Your Turn

Do you use Automated Rules? What kinds of rules do you use?

Let me know in the comments below!

The post A Guide to Automated Rules appeared first on Jon Loomer Digital.

Meta is rolling out Opportunity Score, which represents how optimized your campaigns, ad sets, and ads are.

Where can you find your Opportunity Score? What the heck is it? How is it calculated? And does it mean anything?

Let’s investigate…

Where to Find It

I first realized I had access to Opportunity Score when I noticed it at the top of the Ads Manager table view next to the ad account selection drop-down menu.

It’s a bit random there, if we’re to be honest. Hover over it and you’ll get a breakdown…

You may also find it on your Account Overview page.

You’ll get recommendations that can improve your Opportunity Score if implemented.

What Is It?

Opportunity Score is graded on a 0 to 100 scale and represents how optimized your campaigns, ad sets, and ads are collectively. This score is reflective of all advertising that is active on an ad account and is not specific to a single campaign, ad set, or ad.

Great. So, how does Meta determine whether your account is properly optimized? It’s based entirely on how many delivery recommendations you adopt.

You’ve seen the recommendations. You may have ignored them. They could recommend combining ad sets because Audience Fragmentation or Auction Overlap has become an issue. Or turn on Advantage+ Placements to help with costs. Or apply standard enhancements to improve ad performance.

I’m making some assumptions here. Meta’s details about this are limited. I haven’t seen any documentation that lists out all of the possible recommendations that contribute to this score.

How Is It Calculated?

And now it’s going to get more convoluted. Not every recommendation is weighted equally, and values will be different based on the ad account, objective, aggregated industry insights, and more.

Scores, and factors that contribute to them, update and calculate in real-time. Here’s how Meta explains it:

Certain recommendations impact your score more than others based on how valuable we estimate they may be for your account. This estimated point value varies depending on things like your ad objective, aggregated industry insights and more. Your score updates in near real time, so the actual point change might be higher if you’re no longer eligible for other recommendations or lower if you become eligible for new recommendations.

Meta provides few details and examples, but this is the closest I found when explaining how applying recommendations impacts your Opportunity Score:

For example, you might have a score of 60 that could be improved by fixing audience fragmentation and using Advantage+ placements. When looking at the recommended actions, you might see that fixing audience fragmentation issues may improve your score by 35 points and enabling Advantage+ placements may improve your score by 5 points. In this situation, applying both recommendations could result in a score of 100. If you want to prioritize certain recommendations, you may want to focus on fragmented ad sets because it will likely increase your score more.

It would be nice to have a true list of all of the precise recommendations that contribute to this score, but we don’t have that.

The bottom line is rather simple: If you apply every recommendation that Meta gives you, your Opportunity Score should be 100.

Does It Reflect Performance?

Not necessarily.

Your Opportunity Score literally reflects your ability to adopt delivery recommendations. A high score doesn’t mean that your campaign is performing optimally and a low score doesn’t mean it’s performing poorly. Adopting recommendations to increase your score also doesn’t guarantee you’ll get better results.

That said, the recommendations and values assigned are based on Meta’s models that help highlight what will improve performance.

This is Nonsense… Or Is It?

My initial impressions of the Opportunity Score were that it’s complete nonsense. All it reflects is your willingness to accept delivery recommendations. And there are absolutely times when you should ignore them.

But, let’s look at this from a different angle. If you have a low Opportunity Score and your ads aren’t performing, this gives you some potential reasons why. You have lots of opportunities to make changes that could positively impact your performance.

In particular, I think about how best practices have changed over the years. So many advertisers resist Advantage+ Audience, audience expansion (when it’s an option), and even Advantage+ Placements. They continue to segment targeting into multiple ad sets per campaign like it’s 2018.

I would expect that those who resist these newer best practices will end up with very low Opportunity Scores. Again, it doesn’t necessarily mean they’re getting terrible results, but this could help highlight the specific ways a badly performing account could be improved.

More than anything, this gamifies applying recommendations. It could actually work.

How to Approach Opportunity Score

Remember that your Opportunity Score doesn’t reflect performance. Being “most optimized” or even poorly optimized in the eyes of Meta doesn’t necessarily mean anything.

Its meaning may be more about probability. Meta has a ton of data about what works and what doesn’t. My guess is that a high Opportunity Score is more likely than a low score to perform well. It just doesn’t guarantee it.

I’d also suggest that you don’t completely ignore any recommendation that Meta makes. Try to understand where that recommendation is coming from. Do you resist it? Why? Is it reasonable?

Also, use these recommendations as opportunities to experiment if you aren’t getting great results. You may have resisted them in the past, but what do you have to lose? Maybe you’re just being stubborn and this will help results improve.

I’m not trying to shame you. I know it took me some time to embrace some of Meta’s changes over the years, and I’m still skeptical of some of them. But there comes a point for every advertiser when you need to eventually face the possibility that you’ve been wrong. Consistently bad performance is the blinking red light that should inspire change.

You could laugh off the Opportunity Score as mostly nonsense. I’m not saying that you should obsess over it. But it should be one of the first places you look when you’re struggling to improve results.

Begging for Transparency

This may sound crazy, but I think it’s a reasonable request…

I don’t see any reason why these formulas need to be protected. It’s not that I want to see the specific mathematical equation that led to my score. But a log of every recommendation, whether it was adopted, and the real-time value assigned to it would be helpful.

As we know, these values are dynamic, and they’ll be different by ad account, industry, and situation. Those values will even change from day-to-day. But, seeing them could be extremely helpful.

It could highlight what is often most important. It could also help me understand which changes (whether I’ve implemented them or not) Meta believes are most impactful.

I have a 97 right now. What are all of the things that I did right to get that 97? I’d love to see it.

Your Turn

Do you have Opportunity Score yet? Do you think it will be useful?

Let me know in the comments below!

The post Opportunity Score in Meta Ads Manager appeared first on Jon Loomer Digital.

When you create a sales campaign in Meta Ads Manager, the recommended setup is an Advantage+ Shopping Campaign.

First rolled out in 2023, Advantage+ Shopping Campaigns streamline and simplify the steps necessary for setting up a sales campaign while applying advanced machine learning to ad delivery and optimization.

But these campaigns also represent a drastic departure from the complex campaigns advertisers constructed in years past. Many advertisers doubt the effectiveness of Advantage+ Shopping Campaigns due to their simplistic nature that requires very little input and customization.

I’ve written blog posts and recorded videos about the numerous nuances and changes related to Advantage+ Shopping Campaigns, but this post will help aggregate all of those developments into one place.

Let’s discuss in detail all of what makes these campaigns unique. Consider it a roadmap to create your own…

Locked-In Defaults

Advantage+ Shopping Campaigns were much more restrictive when they first became available. Over time, Meta has allowed a bit more customization.

But, these are still far more restrictive than a manual campaign.

You can’t adjust the objective from Sales, but that should be self-explanatory. Advertisers don’t have the ability to turn on Dynamic Creative. Placements are locked in at Advantage+ Placements, though we’ll get to a minor potential adjustment there. And the age is defaulted to 18 and up.

This sounds more customizable than it is. You’ll see how little control you have over targeting shortly.

Conversion Settings

This section has grown since Advantage+ Shopping Campaigns first became available.

Conversion Location

There are at least two options for Conversion Location: Website or Website and App. Some advertisers also have Website and Shop.

Performance Goal

The performance goal defines what is most important, which ultimately impacts the delivery of your ads. Advertisers have the option of maximizing number or value of conversions.

If you use the default, Meta will try to get you the most conversions within your budget. If you optimize for value, you may get fewer conversions but with a focus on higher dollar value.

Conversion Event

This defines the specific type of conversion that determines success. Originally, the only option was Purchase. But, now you can select from any of your standard or custom events.

Personally, Purchase seems most logical here. But, feel free to experiment with other options.

Bid Strategies

The default bid strategy will be Highest Volume (if maximizing number of conversions) or Highest Value (if maximizing value). The option to use manual bidding was not available initially. Advertisers have the option of setting a Cost Per Result Goal (when maximizing number of conversions) or ROAS Goal (when maximizing value).

Only use these as a last result if you are not getting the performance you want but can spend enough to generate the volume you’ll need to make manual bidding effective.

Attribution Setting

Attribution is how Meta assigns credit to an ad for a conversion. The attribution setting determines two things:

• How conversions are defined for reporting
• How your ads are optimized for delivery

The default attribution setting is 7-day click, 1-day view, and 1-day engaged-view (for videos) — which is the case for manual campaigns, too. This means that Ads Manager will report conversions that happen within 7 days of clicking your ad, one day of viewing (without clicking), or one day of viewing your video for at least 10 seconds without clicking.

Click attribution can be adjusted to 7 days and either view attribution option can be set to “none.”

Targeting

This, more than any other feature, may be what sets Advantage+ Shopping Campaigns apart. Your targeting inputs look like this…

Countries or states. That’s it. No detailed targeting. No custom audiences. No lookalike audiences.

And this has been a major mental block for advertisers. If we can’t define our target audience, how can Meta possibly deliver our ads to the right people?

Well, that’s the beauty of the machine learning that drives these campaigns. Targeting is largely determined by your performance goal (“who is most likely to perform this action?”), pixel data, and conversion history.

Audience Controls

So, you have limited impact on targeting within the Advantage+ Shopping Campaign. But you can do something from the ad account level.

Go to your Ad Account Settings…

If you don’t see sections for Account Controls and Advantage+ Shopping Campaigns, go to your Advertising Settings (a new section that is rolling out).

Audience Controls allow you to set location and minimum age restrictions account-wide. These now apply to all campaigns, not just Advantage+ Shopping Campaigns.

Only use this if there are restrictions regarding where you can do business and whom you can serve.

Within the Advantage+ Shopping Campaigns section of your Advertising Settings, you can define some important audience segments: Existing Customers and Engaged Audience.

Use custom audiences to define each of these groups.

• Existing Customers: Those who have already bought from you
• Engaged Audience: Those who have engaged with your business but have not purchased a product

This information is primarily used for reporting (we’ll get to that). You can’t technically target either of these groups, but…

Existing Customer Budget Cap

When setting your budget, you’ll have the option of establishing an Existing Customer Budget Cap.

This allows you to put a cap on how much of your budget is spent on existing customers, leaving the rest to prospecting. The accuracy of this cap relies heavily on your ability to define your existing customers in Advertising Settings.

Only use this if you want to focus primarily on new customers as a cap will likely lead to less volume of sales.

Reporting

I’m jumping ahead a bit here, only because there’s a reporting feature unique to Advantage+ Shopping Campaigns that relies on the Existing Customers and Engaged Audience audience segments.

Once you publish your campaign, there’s another unique benefit to defining your Existing Customers and Engaged Audience. It allows us to get greater insight into the people who saw our ads — and who converted.

From the Breakdown menu in Ads Manager, go to Delivery and select Audience Type.

This will generate three rows to segment your results by New Customers, Existing Customers, and Engaged Audience.

This is especially helpful for advertisers who distrust the lack of control of algorithmic targeting. Even without inputs, your ads will be distributed to people who have had a connection to your business.

Placement Controls

Earlier, we discussed how there’s a fixed default for Advantage+ Placements. Unlike manual campaigns, you cannot customize placements within the campaign. But there is something you can do in the Advertising Settings.

Placement Controls are found under Audience Controls.

Unlike Audience Controls, which now apply account-wide to all campaigns, Placement Controls only apply to Advantage+ Shopping Campaigns. If your business can only advertise on certain placements, you can remove some options here…

This is an incomplete list, but you can remove some of the placements that have the potential to be problematic.

That said, I discourage advertisers from manually removing placements whenever optimizing for a purchase, unless you have a very good reason for doing so. It’s unlikely to be for performance issues since the algorithm will adjust if a placement isn’t converting.

One Ad Set

Of all of the unique features of Advantage+ Shopping Campaigns, this might be the biggest mental hurdle for advertisers. But when you consider how these campaigns work, it makes sense.

Unlike a typical manual campaign, Advantage+ Shopping combines the campaign and ad set into a single step. You cannot create a second ad set within these campaigns, and that’s intentional.

There’s no reason to create multiple ad sets for different targeting segments since each Advantage+ Shopping Campaign uses wide-open, algorithmic targeting.

There’s very little reason to create multiple ad sets based on optimization. You could conceivably want to test different conversion locations (Website, Website and App, or Website and Shop), performance goals (number of conversions or value), or conversion events, but Meta is clearly discouraging that.

I know that some advertisers insist on creating multiple campaigns to promote different products, but that’s not in line with the point of these campaigns either. The assumption is that you’re going to load up your campaign with creative, whether it be manual ads or catalog ads.

Take a simplified approach here. While there are exceptions to every rule, avoid the urge to create multiple campaigns or ad sets to force Meta to use your outdated strategy.

Schedule Individual Ads

While it would be helpful to have this feature for manual campaigns, it makes sense why it’s unique to Advantage+ Shopping.

Once again, Meta is pushing the one campaign, one ad set approach. As a result, your campaign could be loaded up with ads that promote different products.

If you want to prevent the promotion of different products at the same time or leverage sales and other price changes, an ad schedule may be useful.

When creating an ad, there is an optional Schedule section between Format and Multi-Advertiser Ads.

Focus on Creative

Your impact on the performance of an Advantage+ Shopping Campaign is minimal, up until this point. You can certainly screw some things up, but the best thing you can do is not touch a single setting until you get to the ad. These campaigns are that powerful.

But that doesn’t mean you’re guaranteed good results. You’re not. And a major factor will be your ads. Dedicate 90% of your time to ad copy and creative.

Advantage+ Shopping Campaigns are hungry for creative. Do not settle for a single ad. You can automatically test up to 150 creative combinations. Don’t be worried about overwhelming Meta with too many ads.

Experiment with different formats. Use the multiple text options. Try Catalog Ads. You don’t need separate campaigns for different products. Throw them all into this campaign. That’s what it’s for.

This is your time to shine as an advertiser. Take advantage of it.

Your Turn

Are you running Advantage+ Shopping Campaigns? What do you think?

Let me know in the comments below!

The post Get Started with Advantage+ Shopping Campaigns appeared first on Jon Loomer Digital.

Meta advertisers who promote special ad categories have a challenge. Among the restrictions they face, the biggest complaint is related to the lack of targeting control. But you still can get results using special ad categories.

When creating a campaign, this is one of the first things you’ll need to declare if your promotion falls within one of these categories:

• Credit
• Employment
• Housing
• Social Issues, Elections, or Politics

Once you do, your options within the ad set and ad are adjusted to prevent you from violating rules.

In this post, we’ll discuss the challenges advertisers face when promoting special ad categories and where you should focus to get good results.

The Challenge

One reason for special ad categories is that Meta wants to prevent you from breaking rules that could potentially get them in trouble (and you, of course). We saw this with Cambridge Analytica and the special ad category related to Social Issues, Elections, or Politics. But we also see this regarding discrimination claims related to the special ad categories of Credit, Employment, and Housing.

This post is focused largely on those three since the selection of any of them as a special ad category will significantly impact your targeting control.

Following are examples of how your targeting inputs are restricted:

1. Age: Restricted to 18 to 65+.

2. Gender: Fixed to all genders.

3. Detailed Targeting: Some detailed targeting options will be unavailable. No ability to exclude any detailed targeting.

4. Location: Must include all areas within a 15-mile radius of any location. No ability to target by postal code or zip code.

5. Custom Audiences: You must be sure that your audiences do not discriminate.

6. Lookalike Audiences: Unavailable.

If you found success in these lines of business before special ad categories became a thing, you probably struggled to adjust once these restrictions went into effect. It was a completely different world.

Some failed and gave up. But the reality is that you can still have success with special ad categories. And what’s interesting is that the evolution of Meta ad targeting towards algorithmic audience expansion and fewer targeting inputs may work in your favor.

That said, there are also approaches that are unlikely to work now without some sort of targeting control. But this is true of Meta ad targeting generally now, special ad category or not.

The difference is that while certain strategies no longer work for Meta advertisers generally, you can usually mitigate those issues with targeting inputs. That’s not the case with special ad categories.

Here are some important steps to get the most out of special ad categories…

1. Prioritize Conversions

The challenge faced when promoting special ad categories isn’t uncharted territory. Some of the solutions are rather obvious.

You can’t edit age or gender, you say? No lookalike audiences and limited detailed targeting? That’s… kind of what advertising is now for everyone.

Advantage+ Shopping Campaigns don’t allow for any targeting inputs. Advantage+ Audience, which is the default for all objectives, uses your inputs as suggestions before going much broader.

But, just as is the case when using Advantage+ Shopping, Advantage+ Audience, and any audience expansion, you’re most likely to get the best results when optimizing for some sort of conversion — especially a purchase.

If you’re promoting something related to employment, credit, or housing, make sure to set a performance goal that aligns with a conversion event.

Another option worth considering is using instant forms to optimize for a lead.

If you’re skeptical because you’re worried about quality, hang with me. We’ll get to that.

2. Avoid Top-of-Funnel Optimization

This goes hand in hand with prioritizing conversions. Back in the “good old days,” you could probably find some success optimizing for engagement or link clicks while promoting some of these categories because you could restrict who sees your ads. Those days are over.

And because of that, you’re more likely than ever to get low-quality results and reach irrelevant people. Why? Because Meta’s ad delivery algorithm has no concern for finding people who necessarily care about what you’re offering. It’s only trying to get you as many of the actions as possible that match your performance goal within your budget.

Let’s provide an example related to special ad categories…

You’re trying to promote a job opening and you want to get more applicants. If you optimize for leads, the algorithm will optimize and make adjustments based on getting you more leads. If you optimize for post engagement, the algorithm will focus on getting you people who will engage with your ad.

That engagement could come from anywhere, and the algorithm will make adjustments to make sure that you get more of it if possible. But that doesn’t mean this engagement will come from people who are looking for a job. The algorithm doesn’t care.

The algorithm doesn’t technically care if people are looking for a job when optimizing for a lead either. But it will learn from the people who complete that form to show your ads to more people like them.

3. Define Precisely What You Want

This might be the most important secret to Meta advertising success. When advertisers fail to get good results, they’re quick to point the finger at Meta. But the problem starts with you.

Meta couldn’t get you good results partly because you did a bad job of defining precisely what you want. This is absolutely critical. The algorithm is literal.

That’s reflected in the first two steps. Don’t set a performance goal for post engagement if what you ultimately want is a lead. But it goes deeper than that.

What is your end goal of setting up this campaign? Is it getting a qualified candidate for a job opening? A phone call with a potential home buyer? An application completion for a credit card?

When possible, these are the things you should optimize for. You’ll get less volume, so you’ll need the budget to pull it off. And there may be some additional technical steps to set up.

You can optimize for conversion leads instead of leads, for example.

When you do this, Meta will follow leads through your funnel to see if they ultimately perform a conversion (this requires additional setup and patience).

You could potentially optimize for offline conversions that reflect things like a phone call completed or CRM tag added to a contact. Think of what your goal is and how you measure when that goal happens.

4. Lead Quality 101

As I said earlier, much of the responsibility falls on you to help Meta understand what it is you want so that the ad delivery algorithm can optimize and adjust for that action. You can accomplish that with performance goals. But you can also do things that impact who is able to complete your form. Meta will learn from this and it impacts delivery.

For example, you could provide a streamlined form that only requires first name and email address. You will get more volume of leads this way, but you’ll also get lower quality.

Lead Quality 101 is a balance of quality and quantity. Make your form as quick and easy as possible to complete and you’ll get more leads, but most won’t convert. Create an extremely complicated form that takes time to complete, and you’ll get very few leads — but those who do are more likely to be qualified.

Here are a few strategies you can try to increase your lead quality:

1. Ask more questions.

Make sure that you get more of the information that you need to help determine whether this is a qualified lead. Don’t ask questions for the sake of it, but increase quality by making it slightly more time consuming to complete the form.

2. Ask questions that require longer answers.

One of the benefits of Facebook instant forms is that they can pre-fill some of the personal data into the form fields. But that’s not great for lead quality. Ask questions that will require a thoughtful answer.

3. Use Lead Filtering.

You know that some lead characteristics are qualifying and disqualifying. You can use lead filtering so that if someone provides an answer that disqualifies them, they are unable to complete the form.

4. Don’t use the “More Volume” form type.

When using instant forms, there are three different form types to choose from:

• More Volume
• Higher Intent
• Custom (or Rich Creative)

More Volume will give you a streamlined form, Higher Intent splits it into a few steps, and Rich Creative allows you to build out a robust form with multiple sections.

For all of these tips, keep in mind that some special ad categories have rules related to the types of data you can collect in lead forms. In some cases, you cannot collect personal information such as age, gender, relationship status, and location information.

Craft Copy and Creative Carefully

Let’s stick with the theme.

This isn’t about using engagement bait or click bait to get people clicking our ads. It’s about using copy and creative to make sure that our ads attract the people we most want to click on them.

Be clear about whom your ads are for. Address their needs and pain points and show how your product is the solution.

You do not want your ad to attract everyone. If you create a generic ad that could appeal to all people, you’ll get generic and low-quality results.

Special ad categories may prevent you from accessing certain targeting inputs, but your ads can act as your targeting.

Just be sure that you continue to follow all rules related to special ad categories and discrimination.

Your Turn

Have you had success promoting special ad categories? What strategies have you used?

Let me know in the comments below!

The post How to Get Results Using Special Ad Categories appeared first on Jon Loomer Digital.

There is no single aspect of Meta advertising that has been impacted more during the past year than targeting. The change has been dramatic.

The problem is that advertisers aren’t so quick to move with these changes. They resist, and they’re mostly determined to apply their tried and true targeting strategies from years past.

In some cases, these strategies still work — or work well enough. In others, they fail miserably, and advertisers who misunderstand the current environment can’t figure out why.

During the course of the past year, I’ve published about 30 pieces of content related to the evolution of Meta ads targeting. I highlight the 20 cornerstone pieces below.

Consider this post a deep resource to help walk you through how to approach targeting now and in the future.

On a Macro Level

Let’s begin with a group of posts related to targeting, where we were, where we are now, and what we can expect in the future.

Where we’ve been…

1. The Ultimate Guide to Meta Ads Targeting: Some targeting methods are new and others have been around forever. This post provides a thorough overview of how you can control who sees your ads with targeting inputs.

Where we are now…

2. 6 Targeting Mistakes Advertisers Make: When ads fail due to the decisions made by advertisers related to who should see their ads, it’s usually due to one of these six things.

3. The Evolution of Who Sees Your Ads: So much has changed during the past few years. It’s important that we reframe how we look at “targeting.” It’s now more about who sees our ads, and that’s not always something we determine with targeting inputs.

4. Your Targeting Matters Less Now: This is something that advertisers need to understand and embrace. It’s not that targeting doesn’t matter at all. It’s not that going broad or audience expansion will always work better. It’s that, quite simply, our targeting inputs make less of an impact now than ever before.

5. How to Approach Meta Ads Targeting Now: Accept that things are different now. You can’t approach targeting the same way that you once did. You need a new strategy.

Where we’re going…

6. The Future of Meta Ads Targeting: I don’t have a crystal ball, but I do think I’m a good judge of where we’re going based on trends. And it’s pretty darn obvious.

7. Meta’s Removal of Detailed Targeting is a Reminder of What’s to Come: Meta rarely adds new targeting options. Instead, the news is almost always that targeting options have been taken away. This should be a sign of what is to come.

8. Targeting Will Get More Difficult: If you struggle to embrace the new world of ad targeting and your role in it, there is no relief in sight. If you don’t adjust, it will only get tougher.

9. Will Meta Remove All Interest Targeting? It’s not a crazy question. After all, Advantage+ Shopping strips away virtually all targeting inputs. Interest targeting also gets Meta in trouble at times due to misuse. So, might interest targeting eventually disappear?

Audience Expansion

The biggest changes to targeting during the past year and more are related to the expansion of who sees our ads beyond our targeting inputs — if we provide them at all.

10. Advantage Targeting: How Meta Audience Expansion Products Work: It all started here. I’ll candidly admit that I resisted. I didn’t like the idea that Meta could expand beyond my targeting inputs. Here’s how Advantage audience expansion works in three different forms.

11. Advantage Detailed Targeting Updates: Audience expansion isn’t perfect, and there are times when you should avoid it. Unfortunately, Meta is starting to limit how often you can avoid it.

12. Meta is Forcing Expanded Audiences for Top of Funnel Optimization: In this post, I make the case for why this is a bad change and what Meta needs to do to make audience expansion for top-of-funnel optimization viable.

13. Advantage+ Audience Best Practices Guide: Advantage expansion products may eventually be a thing of the past, replaced by Advantage+ Audience. This approach applies to any objective and uses your targeting inputs — if you provide any — as mere suggestions. This post outlines how this works and how you should approach it.

Today’s Strategies

Most people misunderstand my feelings about Advantage+ Audience and audience expansion. While I truly believe you should embrace and use it in specific situations, it’s also counterproductive in others. It’s a matter of understanding how these things work, what makes them powerful, and when they might fail.

14. Are Audience Suggestions Necessary?: We’ve reached an interesting point where it may make sense, based on on Advantage+ Audience works, not to provide any audience suggestions at all.

15. Should You Restrict by Demographic Group?: Some of these tools force us to confront our approach to targeting. This is a primary example. In the past, it’s been a must to restrict by demographic group to help the algorithm. But there are specific cases now when that may no longer be the case — but others when that restricted is necessary.

16. Ads Reaching the Wrong People?: Advertisers often make claims about ads reaching the wrong people based on comments, but that’s not a good gauge of whether you actually paid to reach them. Here’s what you should do instead.

17. No Gender in Audience Controls: One interesting quirk of Advantage+ Audience is that there are no controls for gender. You can provide gender as an audience suggestions but not as an Audience Control. In some cases, this actually isn’t a big deal. But there are exceptions.

18. When Broad Targeting Fails: While I’m generally looking forward and an advocate for the advancements in Meta ads targeting, there are specific cases when it’s still not ready for prime time. There are reasons it fails, and it’s something that Meta could fix.

19. Going Broad Isn’t Always the Answer: Whenever I write about the newer targeting options, it does not fail. I’ll get comments from people telling me how going broad, using Advantage+ Audience, or turning on audience expansion doesn’t work for them. That might just be the case!

20. When to Switch to Original Audiences: There are times when it does not make sense to use Advantage+ Audience due to weaknesses in how it works. Be aware of these examples because you may find yourself throwing money away. The expansion of your audience will only make what was already a problem much worse.

Your Turn

How have you adjusted to the evolution of Meta ads targeting?

Let me know in the comments below!

The post A Comprehensive Guide to Meta Ads Targeting: 20 Resources appeared first on Jon Loomer Digital.

If you’re a Meta advertiser, you’ve experienced this. You face the task of running ads that will drive more purchases or sign-ups, but they are utterly failing. Your ads aren’t converting at all, or the number of conversions is startlingly low.

It’s easy to blame Meta for your bad performance, but you know that’s a bad approach. Instead, you should troubleshoot to isolate the specific factors that are leading to these bad results so that you can address them.

Stop throwing money away. Your lack of conversions is likely due to at least one of these things…

1. Pixel, API, or Event Problems

If you get this wrong, you have no chance. Events are how important conversions are defined. This makes attribution (credit given to your ad for conversions) possible. And the algorithm learns from those attributed conversions to make adjustments to delivery.

You haven’t set up the pixel or Conversions API.

If you don’t have either set up, what are we even doing? I assume you’ve got the pixel set up — that’s the bare minimum now. But, attribution is bound to be incomplete if you haven’t also set up the Conversions API — either web or CRM version.

You’ve set up events incorrectly.

It’s one thing to have the foundation (pixel and Conversions API) set up properly. That’s worthless window dressing without events.

In some cases, event setup is straightforward. In others, it can be complex. The result could be undercounting, overcounting, or events that haven’t been deduplicated.

This confuses Meta, which will impact your results.

You’re optimizing for the wrong event.

You could have everything set up properly, but the problem could be that you’re optimizing for an event that isn’t your ultimate goal.

Advertisers often do this because they are unable to exit the learning phase by optimizing for their conversion event of choice (like a purchase), so they may optimize instead for something further up the funnel that will generate more volume.

It’s not that this is necessarily something you shouldn’t try. But it’s always a gamble to optimize for an event that isn’t what you ultimately want. More often than not, this results in not getting the thing that will make the campaign successful.

2. Your Performance Goal

A surefire way to get disappointing conversion results is to set a performance goal for something other than a conversion.

The performance goal may be the most important step you take when creating a campaign. It defines what you want to accomplish. This also impacts who sees your ads. The algorithm will dynamically update delivery in an effort to get you more of that action.

If you set a performance goal for link clicks, landing page views, ThruPlay, post engagement, or some other top-of-the-funnel action, don’t be surprised if you struggle to get any conversions.

Why? Meta’s delivery algorithm doesn’t care if you get conversions in that case. The only focus is on getting you those clicks or other actions because that’s what you defined as your performance goal.

If you want conversions, set a performance goal that reflects that.

3. Your Ad Copy or Creative

You could summarize this section by simply saying that if you create a bad ad, you should not expect to get conversions. But, let’s dig a bit deeper.

Understand that people aren’t robots. You can’t just create an ad and expect people to perform the action that you want. You have a role to play.

In fact, ad copy and creative may be more important now than ever before. Since your targeting inputs mean less than they once did, much of the targeting is determined by your ad. You attract your ideal audience.

Here are some examples of how your ad can go wrong…

Your copy doesn’t inspire an action.

This is the most important quality of good copy. It needs to inspire the action that you want. A prospective customer should read your ad and know what they are supposed to do and why.

Your ad doesn’t clearly articulate the value of your product.

What makes your product special? What is the customer’s pain point that your product solves? It’s not always easy to articulate these things in an ad, but that’s your job.

Your copy is unprofessional or is filled with typos.

The audience matters, but there’s often no better way to repel potential customers than an ad that’s littered with typos and grammatical errors. You don’t need to be buttoned up and professional for all audiences, but you still need to convey a trustworthy brand message.

Your creative is fuzzy, out of focus, or poorly done.

Unprofessional execution can be found in the creative, too. You don’t need professionally staged images. Those can be ineffective, too. And while there are arguments for the effectiveness of intentionally ugly ads, the audience matters.

Your creative isn’t optimized by placement.

Your ads will be shown in many different placements with various aspect ratios and design specs. Some of it will be taken care of automatically for you. But, your creative can also be cropped in ways that impact your brand. The copy may also be limited by character counts, thereby impacting your message.

Your ad is bombarded by negative comments that you don’t address.

Do you publish ads and walk away? If you get bombarded with negative comments, you can’t just ignore them. They need to be addressed in some way, or they may be the reason why no one is converting.

4. Ineffective Offer

This is loosely connected to your copy itself, but there is a difference.

You could actually do everything right with your ad, but your offer itself isn’t desirable. Great copy can’t fix a bad offer.

Is the price too high? Is the discount a weak 10% off or free shipping? Did you fail to make your offer irresistible?

You could potentially create an ad with no copy at all. If the image features an amazing offer, it will generate conversions.

Your offer is that important. Take your goggles off. Would you act on your offer? If not, come up with something better.

5. Landing Page Issues

You’re doing everything right. You’ve set up the pixel, Conversions API, and events properly. You created an amazing ad with an inspiring call-to-action and an offer that can’t be refused. But, you still aren’t getting conversions.

It’s probably because of your landing page. And that’s part of the problem for advertisers. You are judged on the performance of your ads, but you may have no control over the landing page experience.

Consider these problems…

Loading and connection issues.

Your ad inspired a potential customer to click. They’re excited. The page loads and loads or eventually crashes. Do not overestimate the potential customer’s patience. They will move on and never come back.

Poorly designed page.

I’ve seen some amazing ads that lead to the cheapest, lowest-quality landing pages. While ugly ads might work sometimes, don’t expect that to be the case for your landing page. You will lose trust.

Confusing or broken purchase flow.

You require multiple steps to complete the purchase, and those steps are unclear. Maybe the customer is unable to easily able to update their cart or apply a promo code. If you make it too complicated, they will leave.

Branding and messaging are inconsistent with your ad.

Do not underestimate the importance of consistency. Colors, branding, and messaging should be consistent from ad to landing page. Was the product or offer that you promised in the ad found on the landing page, or does it look different?

The landing page violates rules related to post-click experiences.

Low-quality post-click experiences like pop-ups, lots of ads, and more can increase your costs, if not get your ads rejected.

If any of these are problems, consider experiences that eliminate, or at least minimize, the landing page. If you need leads, use instant forms. For sales, consider Shops.

6. Product Problems

If you can confidently check off every item we’ve listed so far, you are running out of excuses. The problem might be obvious.

If no one will buy your product, maybe it’s because no one wants to buy your product.

Or maybe the competition in this space is so great that you are unable to stand out. If someone can buy a similar product from a well-known and trusted brand, what makes your product special?

It’s possible the problems go even deeper. Your product has a bad reputation. Bad reviews. Low quality or poor customer service.

These are all issues that are difficult to overcome.

7. CPM Related Issues

When we talk about CPM (Cost Per 1,000 Impressions) related issues in this context, we’re not talking about slight increases that drive up your costs. We’re talking about CPMs that are so high that they’re virtually impossible to overcome.

There are many factors that drive a high CPM:

• Competition for the audience
• Seasonal competition (Black Friday)
• Stale ads with high frequency
• Negative feedback on your ads (hide, report)
• Limiting your audience size unnecessarily
• A difficult or controversial industry

A high CPM gives you fewer impressions for your budget, which will likely mean fewer conversions and potential delivery issues.

8. Your Budget is Too Low

It’s simple. If you can’t spend enough to generate conversions, the delivery algorithm can’t properly learn from the results that it gets. More volume helps the algorithm properly optimize and make adjustments to get you the best results possible.

If you’re generating five conversions per week because you’re spending $20 per day, the algorithm is mostly going blind. It won’t exit the learning phase, and you’ll end up in learning limited.

That doesn’t mean it’s impossible to get results in that state, but performance won’t be stable or optimal.

I realize that not everyone can simply spend more money to get more conversions. But, in some cases, this is self inflicted. You have an excuse if you can only spend $20 per day and it’s all dedicated to one ad set. You don’t have an excuse if you can spend $100 per day, but only $20 is dedicated to the ad set for conversions.

You could combine campaign and ad sets and focus your budget, but you’ve chosen not to.

Your Turn

Are there any other issues I missed?

Let me know in the comments below!

The post 8 Reasons Your Ads Aren’t Converting appeared first on Jon Loomer Digital.

If your business logs important conversion events that happen offline and you run Meta advertising, you should send those offline events using the Conversions API. These offline events can be used for attribution (provide credit to your ads for conversions) and optimization (show ads to people likely to perform that event).

The most common scenario is when you have reps who contact leads in an effort to close sales. If those sales aren’t represented by website conversions, you’ll want to send those to Meta so that they are eligible to appear in your Ads Manager reporting.

Of course, there are countless ways to do this. It’s the biggest issue when communicating how to set up the Conversions API (whether web or CRM). I’m writing this post so that it can apply to the most people possible, requiring Google Sheets and Zapier.

This is a multiple step process, because nothing with Meta can be straight-forward. But, I’m hoping to make it as painless as possible.

In order to follow the steps in this tutorial, you’ll need the following:

• A Google account (for Google Sheets)
• A Meta Business and ad account
• A Zapier account

1. Create an Offline Event Set

From your Business Settings (also known as Business Manager), go to Offline Event Sets under Data Sources.

Click the blue “Add” button. Then name your offline event set and click “Create.”

Select the ad account that you want to connect to the Offline Event Set and save or click “Next.” You can then give individual people access, if necessary.

2. Create an Initial Event Set

You haven’t provided any data yet, but we need to know what data we can provide and in what format. A good way to set this foundation is by creating an initial offline event set.

Go to Events Manager > Data Sources and find the Offline Event Set that you just created.

It won’t have any data in it yet, so click the blue “Upload Events” button.

It will look like this…

We’ll want to go through the steps of uploading a CSV file of offline customers. While you can rely entirely on the automation we set up to do this, manually uploading a couple of records is a good way to confirm that the format is correct.

You can click to view examples of the data and formats that Meta accepts. Hover over data types to get examples.

The easiest path forward may be to download an example CSV file. Meta provides a link to it, otherwise click here.

Delete any columns that you don’t use and fill in with some data — either some dummy data or a few of your customers. Make sure to use formats that Meta accepts.

Save the CSV. Then click the green “Select CSV File” button.

At the top right, click “Next: Map Data.”

Meta will attempt to map your columns to data they accept. Check to make sure they did so properly. If there’s a column that Meta doesn’t recognize, click it to help map it.

Then select what it should be.

If there’s anything Meta should ignore, select that option.

Then click the blue button at the top right for “Next: Review.”

Hopefully, you don’t have any issues. If you’d like to upload this initial data, click “Start Upload.”

3. Create a Google Sheet

Go to Google Sheets and create a new Sheet. Then paste the columns from the initial CSV. Make sure that you maintain the same format that you used in the original upload.

Do not add any new data to this Sheet until you’ve finished creating your Zap. You’ll then want to update this Sheet whenever you have a new offline customer event that you need to report. That can be done either manually or dynamically using a Zap or some other type of automation.

How you do that is up to you, but I won’t cover it here since there are limitless methods you could do that, depending on your CRM and setup. But you could potentially do it by creating another Zap with Zapier.

4. Create a Zap

Create a Zap where the Trigger event uses Google Sheets and the Action event uses Facebook Offline Conversions.

The “Event” that starts the Zap is “New or Updated Spreadsheet Row.”

Select your Google account. Then select the spreadsheet, specific worksheet, and trigger column. It could look something like this…

If you don’t see the spreadsheet that you created, first make sure that you’re logged into the correct account. Otherwise, click to refresh the data.

Test the trigger to make sure that it brings in data.

The action that you’ll want to perform is “Send Offline Event.”

Select your business account. Then select the Event Set. If nothing appears, don’t panic. This is a known problem that has a workaround.

If you are unable to select your Offline Event Set, go back to Events Manager. At the far right of the Data Sources Overview tab, you should see an Event Set ID that is 15 numerical characters long. Copy that.

Back to Zapier. In the Event Set field, there should be an option to enter custom data. Move to that tab and paste the Event Set ID. It will likely say “No matches found” and a link to use that ID that you pasted. Click that.

Select each of the fields that will pull from your Sheet (examples below are dummy data).

If you don’t provide a date and time, it will default to the time of the Zap. If your sheet is updated in realtime, it’s likely fine to keep that blank.

When you’re done, click “Continue” and test the final step.

Is It Working?

Once your Sheet updates, you should begin to see data in Events Manager. Just know that the date of the data is determined by the date used in your Zap.

You won’t see this data immediately, so don’t panic. It may take 30 minutes or an hour once a Zap runs with new data.

Ads Manager Columns

You’ll want to make sure this new data is reflected in your reporting, where possible. Remember that this will only happen if an offline conversion can be attributed to your ad.

Within Ads manager, click the Columns dropdown and select Customize Columns.

Search for the event that is reflected by your offline activity. Let’s say that it’s a Purchase. When you add Purchases as a column, you can check a box for “Offline purchases.”

That new column will then appear in your reporting.

Optimization

If you want to optimize for an offline event, you can create a custom conversion for it. The easiest way to do this is from the Data Sources Overview screen when viewing your offline event set.

Click the green “Create” dropdown menu at the top right and select Custom Conversion.

The data source should be prefilled. Then select the Event. Finally, you’re required to create a rule for when these events should be included in the custom conversion. If you want it to include all, just create a rule that would automatically include them all — like a purchase value that is more than 0.

Watch Video

I also recorded a video walkthrough on this. You can watch it below…

Your Turn

Do you pass offline events using the Conversions API?

Let me know in the comments below!

The post How to Sync Offline Events Using Conversions API appeared first on Jon Loomer Digital.

One of the most common complaints among Meta advertisers is regarding low-quality results. They get results that appear good on the surface. Scratch a bit, and they realize that they’re getting very little for their money.

This is most often found with leads or top-of-the-funnel actions (link clicks, landing page views, post engagement, or ThruPlay). You realize you’re getting empty actions and feel like you’ve been robbed.

Once you understand how everything works, it makes sense why this happens. You’ll see the weaknesses and the specific steps you’ll need to take to make high-quality results more likely.

In this post, I’m going to focus on six of the steps that you can take to control the quality of advertising results.

1. Performance Goal

If I could make this step 1 through 6, I would. It’s simply that important. It explains why this problem happens and how it helps you fix it.

The performance goal is what defines success. It is, quite literally, your goal for measuring performance of your ads.

Example: If your performance goal is “Maximize Link Clicks,” the entire focus for optimization of ad delivery will be on getting you the most link clicks within your budget. There is zero concern for what people do after clicking. Meta isn’t trying to get you “quality” link clicks. The assumption is that you simply want link clicks.

Let’s provide a few examples of how using performance goals can improve result quality, based on what you’re trying to accomplish…

Purchases

Even when optimizing for conversions where the conversion event is a purchase, you can run into this problem. It’s not so much that you’re getting “low quality” results, but they may be low value. Why? The algorithm is literally focused on maximizing your number of purchases.

But you can impact that by changing your performance goal to maximize value instead. The focus then will be on higher value purchases. That may result in fewer conversions, but will likely lead to more revenue.

Leads

Possibly the most common quality results problem of all is related to leads. We’ll address it multiple times in this post. But there are a couple of things you can try from a performance goal perspective.

The problem happens because your performance goal is “Leads.” But that’s not really your goal. Your goal is to increase the number of people who are likely to buy from you. Meta doesn’t know that.

Unless, of course, you optimize for Conversion Leads when using instant forms.

The conversion lead setup process is a long, and potentially frustrating, one. But it can be worth it. It allows you to define your funnel for Meta so that your leads can be followed from registration to an end goal. The algorithm’s focus will be on the eventual purchase, not the initial lead.

If you run ads for website leads, there are things you can try, too. You could optimize for an action that happens after the lead submission. That could be as simple as setting the conversion event as something related to an action that can be taken on the confirmation page (watch a video, click a button, etc.).

I recorded a video once about a creative way to improve the quality of webinar signups. The main thing is to be flexible and strategic.

Traffic

This is the worst one of all. If your performance goal is to maximize link clicks or landing page views, prepare to be disappointed. Unless you significantly restrict your audience, you’re likely to get incredibly low-quality results. Just empty clicks.

But that’s partly your fault. As far as Meta knows, you want landing page views. The algorithm delivered landing page views. The fact that you actually wanted or expected these people to do something else after landing on your website is something that you need to clarify.

It could mean optimizing for a standard event of some kind instead of link clicks or landing page views. Something else I’ve done is optimize for custom events I’ve created that are designed to define quality traffic behavior.

It would be helpful if Meta offered an easier way to optimize delivery for quality traffic and other top-of-the-funnel actions. Absent of that, custom events are your best alternative.

2. Lead Forms

My suggestions related to adjusting the performance goal to improve lead quality may not be reasonable if you’re budget conscious. The reason is that optimizing for conversion leads or some other event that happens after the initial submission will significantly impact volume. And when that happens, a higher budget is a necessity.

If you’re hoping to improve lead quality while continuing to optimize for a basic lead, not all hope is lost. There are several other steps that you can take.

Ask More Questions

This is Lead Generation 101. If you want more leads, ask fewer questions. If you want better (but fewer) leads, ask more questions. By making the form completion more difficult, it will kick out those who weren’t that interested after all. People often become wary about providing too much information. Those who actually complete a form that asks more questions are likely to be better leads.

Ask Custom Questions

Along similar lines as asking more questions, but you could technically ask questions that are all pre-filled using instant forms. Whether you use instant forms or a form on a website, consider asking a question that requires more thought to answer.

This could be sentence or paragraph answers that provide examples or detailed explanations. Those who aren’t that interested won’t bother.

Lead Filtering

This may be the best solution of all. Lead filtering will only allow people to complete your instant form if they answer your questions the way you want them answered.

Once again, it’s all about defining for the algorithm what you want. If only qualified leads are able to complete the form, Meta learns from those completions. This can help optimize to reach more people who are likely to complete it, too.

Avoid “More Volume” Form Type

If you use instant forms, the default form type is “More Volume.” It’s the simplest to complete.

“Higher Intent” takes you through multiple steps, including a confirmation. It may not make a huge difference, but it can help improve quality.

Try Rich Content

Another form type. Rich Content (previously called “Custom”) allows you to create an instant form with up to four sections. The additional information and steps can help improve the quality of your leads.

3. Copy and Creative

This can easily be missed. I’m not the first one to say it, but copy and creative does much of your targeting now — especially in this new world of audience expansion and broad targeting.

If your ideal customer is a specific type of person, craft your copy and creative to speak directly to that person. Appeal to their needs, desires, and pain points.

Craft generic copy and creative that appeals to everyone and expect to attract generic people.

4. Improve Your Offer

This relates to a situation where you offer something of value in exchange for contact information. It can have a huge impact on lead quality.

Make sure that your offer attracts your ideal lead. If you try to build leads by having an iPad giveaway sweepstakes, don’t be surprised when none of your leads buy from you — unless you sell iPads and related devices.

If you are collecting contact information in exchange for something of value, make sure that the something of value is especially desirable to your ideal lead. In fact, make it boring to anyone else.

5. Audience Inputs

I’m placing this way down the list because it’s less important than ever before. But that doesn’t mean that it can’t have an impact.

Sure, if you use Advantage+ Audience, your audience suggestions will likely have very little impact on the quality of your leads. The same can be said if you use original audiences and those inputs are expanded to reach a broader audience.

But, audience expansion can absolutely lead to low-quality results — especially if the result you want isn’t a purchase. When that’s the case, restricting your audience is one of your options.

Of course, your ability to restrict the audience will depend upon the performance goal. Otherwise, take an old school approach by using custom audiences.

Keep in mind that this approach does not scale well, but if your goal is to attract a high quality audience without breaking the bank, this is the way.

6. Manual Placements (Sometimes)

One of the biggest traps for low-quality results is related to weaknesses in placements. It’s actually one of the primary reasons you’ll get misleading results when optimizing for link clicks and landing page views.

Audience Network is notorious for attracting accidental clicks, bots, and click fraud (before it’s detected). If you optimize for link clicks or landing page views, the algorithm will go straight to this placement to get those clicks because the assumption is that’s what you want. You’ll get lots of them, and they’ll be cheap.

You’ll run into something similar if you optimize for ThruPlay. Meta will spend most of your budget in the Audience Network Rewarded Video placement, and you’ll get results that seem too good to be true.

They seem too good to be true because they are. These people are incentivized to watch your video to get something of value in exchange. Apps monetize themselves with this placement. So, game players may be asked to watch a video to get access to virtual currency. You’ll find these people never do anything beyond watching your video.

The reaction may be to simply remove Audience Network in all cases. But that’s not necessarily the solution either. The reason you should remove it is directly related to your performance goal and whether there are weaknesses in that placement that would be exploited to get that result.

Otherwise, you should generally use Advantage+ Placements when optimizing for any type of conversion. Remove a placement that you know is the direct source of low-quality results.

Of course, that’s not a great solution either because there’s typically a bigger issue at play. Removing these placements may help, but it won’t eliminate it entirely.

You could use News Feed only. If your performance goal is link clicks or landing page views, you’re still going to get cheap, low-quality traffic. It just won’t be as terrible as if you kept Audience Network.

You Have Control

Ultimately, it’s easy to blame Meta for getting you low-quality results. But it’s much less likely to happen if you take the proper steps to prevent it.

Set the performance goal that actually defines what you want — don’t assume that one action will naturally lead to another. Create ads and offers that attract your target customer.

After that, simply know how ad distribution works, it’s strengths and weaknesses. You’ll be better equipped to avoid, detect, and fix problems related to low-quality results.

Your Turn

What steps do you take to improve the quality of your results?

Let me know in the comments below!

The post 6 Ways to Fix Low-Quality Advertising Results appeared first on Jon Loomer Digital.

Meta has begun to roll out an update to ad sets utilizing performance goals for link clicks and landing page views, which was originally announced in January. When using original audiences, Advantage Detailed Targeting is automatically applied.

If you missed that Advantage Detailed Targeting was turned on, you’d be forgiven. This design variation is not at all obvious. If you miss the new label, you won’t see that the audience may expand unless you hover over one of the tooltips.

This is a departure from the primary design I’ve seen when using conversion performance goals. In those cases, a message is highlighted in gray.

But, let’s back up. There’s plenty to unpack here. The signs are all around us that we’re headed towards a future of less targeting control, regardless of the performance goal. And that could be a problem, unless Meta makes some much-needed improvements.

In this post, let’s discuss:

• The current state of audience expansion
• Where expansion is effective
• Where expansion fails
• Where this is headed
• What Meta needs to do

At the bottom of this post, I’ve also recorded a video that summarizes what is going on.

Current State of Audience Expansion

Meta first unveiled audience expansion in 2021 with a suite of products that would eventually fall under the “Advantage” line. Here is how they work…

Advantage Detailed Targeting

Advertisers provide detailed targeting inputs that Meta prioritizes. Your audience can be expanded to reach people beyond that group if better results can be found.

Not long after its initial rollout, Advantage Detailed Targeting became a fixed default for any conversion-related performance goal. Otherwise, advertisers had the option of turning it on or off.

That, of course, changed with this latest rollout of Advantage Detailed Targeting for ad sets utilizing link clicks or landing page views performance goals.

Advantage Lookalike

The second of the Advantage expansion family, Advantage Lookalike works in a similar manner as Advantage Detailed Targeting. If Meta detects that better results can be found beyond the selected percentage of your lookalike audience, the percentage can be expanded.

For example, if you use a 1% lookalike, the audience could be expanded to anywhere from 2 to 10%.

Like Advantage Detailed Targeting, Advantage Lookalike is turned on by default for conversion performance goals and cannot be turned off.

The latest update to link click and landing page view performance goals has not been applied to lookalike audiences. Advertisers still have the option of turning this on or off in that case (for now).

Advantage Custom Audience

Next, Meta rolled out the ability to expand custom audiences if better results can be found. Unlike the first two features, there is always an option to turn Advantage Custom Audience on or off. There isn’t currently a case where it’s on by default (though this may change).

Of course, Meta then took things even further…

Advantage+ Audience

Beginning in August of 2023, Advantage+ Audience became the default way of selecting an audience in the ad set. Advertisers still have the ability to switch back to original audiences, where the three Advantage expansion tools may be applied.

When using Advantage+ Audience, any targeting inputs provided are seen as mere suggestions. You will reach people beyond that initial group, and providing suggestions is optional. If you don’t provide them, Meta will automatically begin with your pixel data, conversion history, and prior engagement with ads as a guide.

Advantage+ Audience is the initial default for all campaign objectives, regardless of the performance goal. When used, any targeting inputs — custom audiences, lookalike audiences, detailed targeting, and even gender and age maximum — are seen as audience suggestions, and your ads may reach people beyond those groups.

Where Expansion is Effective

While I initially resisted audience expansion (“I only want to reach the people I’m targeting!”), I’ve come around to it. But, it’s most effective for a unique set of circumstances.

Audience expansion (any of the Advantage expansion tools or Advantage+ Audience) can work because the algorithm is hyper-focused on finding your desired action, as defined by the performance goal. Your targeting constraints could conceivably restrict the algorithm from getting more of those actions.

This is especially true when optimizing for purchases.

Success is defined by getting more purchases within your budget. If your targeting can be expanded to find more purchases, that’s a good thing.

There’s no better example of this in action than Advantage+ Shopping Campaigns. Targeting inputs are virtually nonexistent, and yet Meta says that they lead to a 17% improvement in cost per acquisition and a 32% increase in return on ad spend.

Where Expansion Fails

For the same reason that audience expansion can be effective for purchase optimization, it often fails for anything else — especially when using a performance goal that represents a top-of-the-funnel action (link clicks, landing page views, ThruPlay, post engagement, and more).

The audience will expand beyond your inputs if more of the actions defined by the performance goal can be found.

This isn’t a problem when optimizing for purchases because getting the purchase is the ultimate determinant of success. The algorithm makes adjustments based on whether it can get you more purchases.

It’s a problem for everything else because quality then matters…

Your audience is expanded to get more link clicks or landing page views. But did these people do anything else after clicking? Were they bots? Where they accidental clicks? Were they people who click everything? The algorithm doesn’t care.

Your audience is expanded to get more people to engage with your post. But is this positive or negative engagement? Do they fit your typical customer profile? Is there any chance that they’d ever buy from you? The algorithm doesn’t care.

Your audience is expanded to get more leads. But were the email addresses provided valid? Are these people reachable? Will they open their messages and engage? Is there any chance they’d ever buy from you? The algorithm doesn’t care (unless you optimize for conversion leads, which isn’t reasonable for everyone).

In each case, you care. And that’s the problem. Audience expansion fails when there’s no control for quality. Your targeting inputs were the only remaining constraints to focus only on potential customers.

Where This is Headed

Look to the most recent developments to predict where this is heading…

1. Advantage+ Shopping Campaigns don’t allow for any targeting inputs.

2. Advantage+ Audience is now the default, and you’re discouraged from switching to original audiences.

3. Advantage Detailed Targeting is now on and can’t be turned off when using link click and landing page view performance goals.

Every new update puts less importance on your targeting inputs. More ways to expand the audience. Fewer controls to be able to target an exact group.

Given that Advantage+ Audience is the default for all objectives and performance goals now, I’m actually surprised that Meta would make this update to Advantage Detailed Targeting related to link clicks and landing page views.

My assumption is that the ability to switch back to original audiences (and utilize Advantage Detailed Targeting, Advantage Lookalike, and Advantage Custom Audience) will eventually be eliminated. But, maybe this is a sign that such a move is further off in the future than I expect.

The bottom line is that Meta isn’t going to stop expanding audiences beyond your targeting inputs any time soon. We’re likely to see this forced for more objectives and performance goals in the future, even if you’ll be able to continue switching back to original audiences.

What Meta Needs to Do

I am not a fan of this latest update to Advantage Detailed Targeting. The reason can be found within the section about when audience expansion fails.

Optimizing for top-of-funnel actions is already problematic. But if Meta removes or de-emphasizes targeting constraints, we lose all checks on quality. It no longer matters who these people are. Meta only cares that they’ll perform the action that we want.

The solution isn’t that complicated, and it’s been needed for years. The evolution of audience expansion only makes it more imperative that Meta act on it.

There must be a way to optimize for quality top-of-funnel actions.

I’d be much more willing to use the link click or landing page view performance goals to promote my blog posts if I could require the algorithm to optimize for quality traffic — not just any traffic. This could be defined by time spent on the website, scroll depth, other conversions, and return visits.

I’d be much more willing to use performance goals related to post engagement if I could require the algorithm to optimize for quality engagement — not just any engagement. I want people who are likely to share my posts, provide thoughtful comments, and return to my content later.

This “quality” element could be an option when setting a performance goal. Do you care more about getting a high volume of actions? Leave it at the default. Do you care about quality? Check this box and expect to spend more.

If that were possible, the expansion of your audience becomes less problematic. The algorithm would expand to get more of the quality actions that you are wanting — and that is ultimately what would guide ad delivery.

This would seem like a natural solution that is good for everyone. Most importantly, advertisers would be willing to spend much more on actions other than conversions if there were an increased confidence in the quality.

Watch Video

I recorded a video about this, too, and you can watch it below…

Your Turn

Do you run ad sets optimized for link clicks and landing page views? What do you think about this update?

Let me know in the comments below!

The post Meta is Forcing Expanded Audiences for Top of Funnel Optimization appeared first on Jon Loomer Digital.

Ad quality is an important factor in the Meta ad auction. It could be the difference when given the choice of two ads to show.

While this is something to consider from an ad-to-ad basis, it’s also a potentially much bigger problem if you make a habit of creating low-quality ads. Per Meta:

In certain instances, if you repeatedly post policy-violating or lower quality ads, our systems may start considering all ads from your Page, domain, ad account or other associated entities as lower quality.

This could become a long-term problem. But Meta does say that if you correct course, your ad performance should improve “over time.”

When considering ad quality, Meta’s systems also look beyond the ad to the post-click experience (like the landing page). Do not ignore the landing page when addressing ad quality.

In this post, you’ll learn some specific examples of the following:

• Low-quality ad content
• Low-quality post-click experiences
• User signals
• Low Quality or Disruptive Content advertising policy

At the end, I’ll provide recommendations on how to address ad quality.

Low-Quality Ad Content

First, you need to avoid specific uses of copy and language in your ad that will flag it as low quality.

These are things that are generally allowed, but within reason. What you’ll eventually find at the end of this post is that any of these things in excess will be considered an ad policy violation that will get your ads rejected.

1. Withholding information.

In other words, “clickbait.” We see organic content like this all the time. There’s some big, shocking news story, but the headline and post leave out important details. If we want to clear up what actually happened, we have to click.

As a sports nut, I see this all the time (again, not with ads but organic content). A shared link with a featured image that doesn’t clearly depict a specific player. A headline and maybe primary text about a rumor or transaction related to this unnamed player. If you want to know who it is, you need to click.

It doesn’t mean that everything needs to be in your primary text, featured image, and headline. But if you are clearly omitting important information in an attempt to inspire the click, it will qualify as low quality.

Here are a couple of great examples that Meta shared…

2. Sensationalized language.

Another form of clickbait, but this form of low-quality ad content is specific to exaggerated text and headlines. Some things actually are shocking. But if the sensationalized text inspires a click and the actual content doesn’t follow through with a shocking story, it can be classified as low-quality ad content.

Here’s an example from Meta related to “MIND-BLOWING uses of carrots!”

3. Engagement bait.

This would include ads that inspire or request actions (typically comments, shares, likes, and other reactions) in an unnatural way. Once again, we see this often with organic content. You may even benefit from it. But it may work against you when running ads.

LIKE if you like baseball, LOVE if you’re a Brewers fan, comment “YES” if you’re both, and SHARE if the Brewers are going to the World Series this season.

Maybe that’s over the top. But here are a couple of examples from Meta…

Low-Quality Post-Click Experiences

Sometimes, your ad is fine but it’s your landing page that is the problem. As was the case with low-quality ads, the following post-click experiences are technically allowed, within reason, but they could impact your ad costs. If your use of these things is extreme, it could get your ads rejected.

We’ll get to the similarities between these examples and Meta’s own ad policy at the bottom of this post.

1. Lack substantive or original content.

Meta doesn’t provide specific examples of this, but I assume this could include a wide variety of problematic content. Maybe you direct to stolen content or the page has basically nothing on it of value.

How quality is measured related to “substantive” is unclear. But if you direct to a very simple landing page, keep this in mind.

2. Disproportionate volume of ads relative to content.

It’s not uncommon for websites to monetize themselves with ads, so that isn’t a problem in itself. The problem is when those ads become “disproportionate.”

Once again, Meta doesn’t define this so that we know what percentage of real estate would qualify, but keep it in mind. I know that some advertisers send traffic to their website for the sole purpose of collecting on ad revenue. If you overdo it here, it could increase your costs.

3. Pop-up ads or interstitial ads.

I have pop-up ads. You may have even seen one while reading this post. That doesn’t make my website unique.

Look, I hate pop-ups, too. Unfortunately, they remain very effective. And when I turned them off for a year or two, I felt it.

Once again, pop-up ads are allowed. Your Meta ads won’t be rejected if you send people to a landing page with a pop-up ad. You may not even see a noticeable difference in costs. But it’s another factor that will contribute to whether the experience is considered low-quality.

4. Unexpected content experiences.

The example Meta provided is “spreading an article’s content across multiple pages and requiring someone to click and/or load multiple pages to read through the full article.”

This makes me think of lists and other popular types of content that don’t allow you to read the full piece in one page. The website benefits from clicks, so you’re forced to click multiple times to keep reading.

I don’t know if this includes lazy loading pages where only a portion of the page loads and you need to click to keep reading and make the remaining article visible.

5. Misleading experiences.

According to Meta’s examples, this tends to apply to negative shopping experiences: Landing page content that misrepresents products, shipping times, or other customer support issues.

This one again isn’t all that clear, but it’s ultimately related to a bad customer experience that happens post-click.

User Signals

Many of the examples so far may be detected automatically from Meta’s systems. But there are also ways that users can notify Meta of problems related to low-quality ads and post-click experiences.

1. Hiding ads.

Specifically, three different actions that users can take:

• Hide ad
• Hide all ads from this advertiser
• Hide ad due to repetition

2. Report ads.

You can report ads for a long list of reasons that would be signals of low quality.

I know that some advertisers are probably wary of user reports contributing to Meta’s quality signals, but it’s safe to say that any ad — no matter how innocent — will get negative responses. Some people simply hate all ads and will report or hide them all. They have unreasonable expectations.

The problem will be if Meta receives an abnormal rate of these reports on your ads.

3. Landing page activity.

Specifically:

• Landing page bounce rate
• Landing page dwell time

This makes sense, specifically tied to clickbait and post-click experiences. Maybe the ad inspired an action, but the landing page didn’t follow through. Or maybe the experience on the landing page was so bad (pop-ups, high volume of ads, generally low quality) that you immediately abandon.

Low Quality or Disruptive Content advertising policy

The content above is related to low-quality, but allowed, ad content. Too much of it can negatively impact delivery and costs.

But Meta also has an advertising policy regarding restricted Low Quality or Disruptive Content. If you violate any of these policies, your ads may be rejected.

1. Examples of restricted low-quality ad content.

Images that are excessively cropped to force you to click to view more: This reminds me of what was a popular organic post type that has seemed to mysteriously disappear. It relied on large images that were broken into multiple parts, and you typically could only see one or two of those parts.

This wouldn’t just be considered low-quality, it would violate this advertising policy and should get your ad rejected.

Deceptive or exaggerated ad text that incentivizes people to click on the ad: Okay, so this is confusing. This sounds like clickbait, which was defined among the low-quality ad examples that are technically allowed, though they will likely impact costs.

Here’s an explanation from the low-quality ad content page:

My interpretation (the best I can, at least) is that there are varying levels of deception. To a point, it’s allowed but could impact your costs negatively. Once you cross that imaginary line, it could get your ad rejected.

2. Examples of restricted destination page content.

Some of Meta’s examples are obvious:

• Sexually suggestive or shocking content on the destination page
• Featuring malicious or deceptive ads on destination pages

But the rest just sound like extreme examples of low-quality post-click experiences:

• A high ratio of ads relative to content on the destination page
• Designing destination pages for the primary purpose of showing ads
• Using excessive popup ads, interstitial ads or poor ad formatting on destination pages

So, again, avoid sending people to pages with a high density of ads. You can use pop-ups, but they shouldn’t be “excessive.”

Recommendations

As you can see, these guidelines aren’t always crystal clear and the levels of severity are open to interpretation. Depending on the low-quality infraction, it may result in higher ad costs or get your ad rejected. Repeat violations may flag your page or account, and it could take time to recover.

It’s always recommended that you avoid toeing these lines of gray area. You might even see some benefits (at least organically) by doing some of these things — though those benefits may not last forever.

Bottom line: While it’s not easy to define what is and isn’t allowed, it’s ultimately not that complicated.

1. Don’t create clickbait.
2. Don’t create engage bait.
3. Don’t create landing pages that are filled with ads.
4. Don’t create bad user experiences.

Here are Meta’s three primary tips for complying with these policies:

1. Link to landing pages that include a significant amount of original content relevant to the ad

2. Minimize the amount of content that blocks or prevents people from viewing the original text on the landing page

3. Display the entire article on the primary landing page

These are very reasonable expectations.

Your Turn

What are your experiences with low-quality ad experiences?

Let me know in the comments below!

The post Low-Quality Ad Content and Post-Click Experiences appeared first on Jon Loomer Digital.