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.

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.

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.

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.

While pondering the changes related to targeting and optimization over the years, it struck we why so many advertisers struggle with understanding how their role has evolved with targeting: There’s a messaging problem.

I know there’s a messaging problem because I was dealing with it myself while I was trying to communicate it. The processes of targeting and optimization are beginning to blend into one. I think I found the solution.

We need to shift our focus to who sees our ads.

Sometimes people see your ads because they were included in your targeting inputs. Sometimes it’s due to Meta’s optimization for delivery. Both have been important. But the importance of both are changing.

Targeting and optimization were previously very different things. Now they are converging.

Maybe this doesn’t make sense yet. But once it does, it will help you better understand the systems at play which determine who sees your ads — and your role in them.

How People Saw Your Ads Pre-Expansion

Previously, advertisers had a critical role when it came to who saw their ads. They provided the initial targeting inputs.

Facebook (before there was Meta) then optimized to show your ads to people within that initial audience who were most likely to perform your desired action. This was “Optimization for Ad Delivery.”

Both were critically important. But optimization couldn’t fix bad targeting. If you provided a flawed pool of people to work with, you would not get good results.

For years, I contended that targeting was the most important advertiser responsibility. It could make or break your advertising.

How People See Your Ads with Expansion

That started to change pretty dramatically once Meta introduced Detailed Targeting Expansion (which eventually became Advantage Detailed Targeting).

Advantage Lookalike and Advantage Custom Audience soon followed.

The advertiser provides the initial targeting inputs. Just as important, they indicate a performance goal.

In some cases, the advertiser has the option to turn expansion on. In others (like when optimizing for conversions), it’s on by default and can’t be turned off.

When on, your initial inputs will be prioritized. But if Meta believes that you can get better results (determined by your performance goal) by expanding the audience, people who would not have qualified within your targeting inputs can see your ads.

The level of transparency has mostly been zero. Until recently, advertisers had no way to know how many of the people reached were via targeting inputs how how many were due to expansion. That’s at least partially corrected with the introduction of Audience Segments.

How People See Your Ads with Advantage+ Audience

While the mechanics of Advantage+ Audience sound very similar to expansion via Advantage Detailed Targeting, Advantage Lookalike, and Advantage Custom Audience, there are some very important differences.

Any inputs you provide when using Advantage+ Audience are mere audience suggestions.

If you don’t provide any suggestions, Meta will start with your prior conversions, pixel data, and previous engagement with your ads. In other words, the targeting will prioritize remarketing without providing inputs.

Another difference from Advantage expansion is that after prioritizing that initial audience, it can go much broader. The focus will be showing your ads to people most likely to perform the action that you want (defined by the performance goal).

As is the case with Advantage expansion, there is minimal transparency regarding a breakdown of performance between your inputs and the algorithmically generated audience. But one can assume that a much larger percentage of those reached are found by the algorithm — especially since you don’t need to provide inputs at all.

How People See Your Ads with Advantage+ Shopping

Advantage+ Shopping Campaigns take this even further. The targeting inputs you can provide are virtually nonexistent. No interests, custom audiences, or lookalike audiences. You can restrict by country and set a current customer cap by defining your current customers in your ad account. But that’s it.

Otherwise, the people who will see your ads are determined via machine learning. All Advantage+ Shopping Campaigns utilize a conversions performance goal (either “most conversions” or “value of conversions“), and the conversion event will define which specific action determines success. This was previously locked in as Purchase, but you can now select any standard or custom event.

Who will see your ads? This is determined using machine learning based primarily on the conversion event.

The Performance Goal is Your Targeting Now

There’s a very good argument (okay, it’s my argument) that the performance goal is more important to who sees your ads than your actual targeting inputs. Especially now that your inputs are only suggestions with Advantage+ Audience and no inputs are provided with Advantage+ Shopping, it’s difficult to make the case that these inputs are as important as they once were.

But that doesn’t mean that you don’t have any role when it comes to determining who sees your ads. Even when you have no targeting inputs at all, like with Advantage+ Shopping Campaigns, there remains one very critical step.

Your performance goal is the targeting now.

If you want purchases, set a conversions performance gaol with Purchase as your conversion event.

If you want post engagement, set that as your performance goal. But don’t expect purchases.

This will automatically include some of the people you would normally target manually via remarketing audiences. The rest are filled in algorithmically based on the performance goal.

But here is something you need to understand: The audience won’t always be the same.

The people who see your ads when the performance goal is Conversions (with Purchase conversion event) will not be the same as the people who see your ads when your performance goal is Post Engagement. Your performance goal determines what you care about — and that is the central lever for determining how Meta optimizes and makes adjustments.

If your performance goal is for anything top of funnel (link clicks, landing page views, Post Engagement, or ThruPlay), you are very likely to run into quality issues. The reason is that Meta doesn’t care whether these people do anything else — because the assumption is that you don’t either. So your ads will be shown to people most likely to perform that action, which could be because they click on everything or a placement often results in that action.

The Role of Ad Copy and Creative

It’s popular to say that targeting has moved to your ad copy and creative (I even said it). While what you do with the ad is absolutely important, I contend it remains secondary to the performance goal.

That’s not to diminish the importance of ad copy and creative. It may be splitting hairs to say that one is more important than the other.

If you pick the wrong performance goal, you’ll need the perfect ad copy and creative to get any results.

If you create a sub-par ad, the right performance goal can help get you some results.

In both cases, your potential is limited. You’ll get the best results by setting the appropriate performance goal and being on top of your game with ad copy and creative.

The Future of Who Sees Your Ads

If you’re following the trends outlined here, it shouldn’t be all that difficult to predict the future of targeting. The continued focuses on privacy, tracking, and malicious uses of targeting (discrimination and manipulation of elections) makes the continuation of this trend a near certainty.

You may argue that your inputs still mean a lot because you use the original targeting options and don’t always optimize for conversions. You regularly find ways to avoid audience expansion.

But do not expect these options to remain. Meta clearly wants advertisers to use Advantage+ Audience. It couldn’t be more obvious that the original methods are on the way out.

And we’ll very likely see the hands-off targeting approach of Advantage+ Shopping Campaigns expanded to other objectives. Meta already hinted at this related to leads.

If you haven’t already started to shift from “targeting” to “people who see my ads,” it will be forced on you eventually. Might as well get used to it.

Your Turn

How do you see your role in who sees your ads?

Let me know in the comments below!

The post The Evolution of Who Sees Your Ads appeared first on Jon Loomer Digital.

Meta advertising has changed rapidly the past few years, and that leads to several common targeting mistakes. These errors are largely due to a combination of ignorance and stubbornness.

I admit that I miss the old days of Facebook advertising — before it was Meta advertising. More than anyone, I preached the gospel of targeting and the art of finding your ideal audience. I found great success with micro-targeting and I found great enjoyment in all of the levers I could pull with targeting to find what works and what doesn’t.

But things are changing. And while I was initially resistant to much of the change, I’ve grown to embrace it. You should, too.

If you’re making mistakes with targeting now, it’s likely one of these six things. And it’s impacting your results…

Improper Use of Exclusions

The improper use of exclusions can go two ways.

1. Nonexistent or incomplete use of exclusions.

The use of exclusions is a fundamental way to avoid wasted ad spend. It’s a step that’s often missed by beginner advertisers.

If you’re promoting a product that can only be purchased once, there’s no need to show ads to people who have already purchased it. If I’m promoting my Power Hitters Club – Elite membership, I will excluded current members using a custom audience exclusion.

While that customer list custom audience is a start, it’s unlikely to exclude all current members due to matching incompleteness. When an exclusion is required, you should exclude that group in as many ways as possible.

An example is if you ever run lead ads using instant forms while also having a landing page on your website, there are at least three different ways you can exclude people who already performed this action: Lead form custom audience, website custom audience, and customer list custom audience.

2. Overuse of exclusions.

While you should use exclusions, you can overdo it. It’s not uncommon for advertisers to exclude all current customers when promoting a product that current customers can buy. They consider it a “true prospecting” campaign and only go after completely new customers.

This is missing a golden opportunity. Your satisfied customers are the ones who are most likely to buy again and again. Excluding them eliminates the least challenging sale.

The response from those who take this approach is that they have a separate ad set for remarketing. But if you have one ad set for broad remarketing and one for prospecting, you’re going to drastically increase the costs to reach your remarketing audience. Remarketing audiences are small audiences, which translates to higher frequencies and CPMs.

It’s inefficient and unnecessary now. Don’t exclude current customers unless those customers can’t buy the product you’re promoting.

Expansion Ignorance

Many advertisers hate hearing this, but your targeting inputs mean less than ever before. This isn’t to say you should remove all targeting inputs and go completely broad (though it’s something to try). But even when you do provide inputs, the targeting is often going broader.

Either advertisers don’t know or they’re willfully ignorant about the role of audience expansion. And it doesn’t necessarily matter whether you’re using the original audience options or Advantage+ Audience.

1. Original audience options.

You’re resistant to the newfangled targeting of Advantage+ Audience and insist on kicking it old school. So you opt-out of it by making a couple of extra clicks to use the original audience options. You even click past the “Are you sure?” message about how it could lead to higher costs.

You enter in a bunch of interests and behaviors. This is how to go after your ideal customer, you think. These detailed targeting options define the exact person you want to reach. You’re doing something super smart.

But, you’re also optimizing for conversions, link clicks, or landing page views. And when you do that, your audience is automatically expanded using Advantage Detailed Targeting.

2. Advantage+ Audience.

It’s possible you may not even know there is a “new way” and “old way.” You spend significant time and budget trying to find the ideal targeting using custom audiences, lookalike audiences, and detailed targeting.

But, guess what? This targeting is only a suggestion.

It doesn’t matter whether you’re optimizing for conversions, link clicks, or landing page views. It doesn’t matter whether you’re using custom audiences, lookalike audiences, or if you click a box to expand the audience.

Your inputs are only suggestions and people well beyond this group will see your ads.

Your inability to understand and appreciate that targeting is expanding beyond your inputs may not be a mistake in and of itself. But this will lead to mistakes as well as wasted budget and time.

Too Narrow When Optimizing for Conversions

Many advertisers treat targeting like it’s 2017. There’s no better example than when optimizing for any type of conversion.

There was a time when a critical step was picking the targeting. Which interests, behaviors, lookalike audiences, or custom audiences made a huge difference to your results?

But when you’re optimizing for conversions now, your targeting inputs aren’t nearly as important as they once were. This is seen in the examples above when running manual Sales campaigns using either Advantage+ Audience or the original audience options, as described in the previous section.

But Advantage+ Shopping Campaigns go even further. You don’t provide any targeting inputs in this case. Meta does it all automatically.

There are two important factors that contribute to how your audience is chosen…

1. Performance goal optimization.

In the case of Advantage+ Shopping Campaigns, it’s typically a purchase (though it can be any standard or custom event now). The algorithm’s primary focus for delivery is to get you as many of that goal action as possible within your budget.

Success is determined by the ability to satisfy that goal. Adjustments will be made to delivery to get you more of those actions where possible.

2. Prior activity.

Whether you’re using Advantage+ Audience without targeting inputs or creating an Advantage+ Shopping Campaign, the initial focus of targeting is determined for you based on your pixel activity, conversion history, and prior engagement with your ads.

The mistake is that advertisers go far too narrow when optimizing for conversions when it simply isn’t necessary. Your biggest obstacle to success is limited budget and audience size. The more you limit the audience, the more you will restrict the algorithm and drive up your costs.

It’s also not as easy to go narrow as it once was, for the reasons already described. In some cases, your attempts are futile and the audience will expand anyway.

But, if you provide broad custom audiences while using the original audiences and turn off Advantage Custom Audience, you are likely doing more harm than good. You may get some short-term results. But you’ll exhaust that audience and run into a ceiling quickly.

It’s an obstacle that’s easily avoidable since Meta will automatically go after relevant people based on pixel activity, conversion data, and ad activity anyway — if you simply allow it.

Overdoing Demographic Granularity

Once again, there was a time and place for this. Especially when optimizing for any type of conversion, those times have passed.

We all did this years ago, and it was smart advertising at the time. We constructed the profile of our ideal customer. Their likes and dislikes, age range and gender, even their incomes and zip codes.

You may have even run breakdowns to find the groups of people by age and gender that lead to the best results so that you can then focus only on them.

You think that’s necessary now, but it just isn’t.

I’ve written before about how this may be necessary when optimizing for top of the funnel actions. But if we’re to be honest, nearly all top of funnel advertising is flawed anyway.

It’s one thing if you are unable to sell to customers under a certain age. Or your product is for women. There’s no reason to get cute messing with these settings simply because you believe that your product appeals more to men between the ages of 35-44.

If your goal is to drive more purchases, don’t try to outsmart the algorithm. It will learn. By restricting options, you are likely driving up costs unnecessarily — and limiting your pool of potential customers.

Too Broad When Optimizing for Top of Funnel

I alluded to it above. Avoid restricting your audience unnecessarily when optimizing for any type of conversion (especially a purchase). But that changes when optimizing for top of funnel actions.

Why? Because ad set optimization is literal. The algorithm’s only goal will be to get the action that you want. And while that is why you should limit restrictions when optimizing for conversions, it’s why top of funnel optimization can fail spectacularly.

Let’s say you’re optimizing for post engagement. You are a women’s clothing brand. You are hoping to attract potential customers by showcasing your new line.

Because you optimized for post engagement, the algorithm will only care about getting you engagement. It doesn’t matter (to Meta) whether that engagement is from a potential customer or not.

So, you’ll get plenty of engagement if you don’t limit by gender. Comments, video views, reactions, and image clicks. But you can bet that the vast majority of this engagement won’t be helpful.

You have to put guardrails on targeting when optimizing for these top of funnel actions because after all of these years, there are still very few ways to optimize for high quality actions that aren’t conversions.

I realize this sounds like a contradiction. I’ve given two very opposite sets of advice: 1. Stop restricting your targeting, and 2. Restrict your targeting. But the important context is whether you’re optimizing for the top or bottom of the funnel.

On one hand, I’d tell you it may be best to avoid running campaigns for engagement or clicks at all. But if you do, you’d better use some strict targeting — and make sure that the audience can’t be expanded.

Unnecessary Extra Ad Sets for Cold Targeting

This is connected to expansion ignorance. It’s also related to advertisers’ refusal to evolve with how things work now.

I avoid making absolute statements like “you should never create multiple ad sets for cold targeting now,” so I won’t do that here. If you’ve found success doing it that way and you aren’t getting results by combining those ad sets, do what works for you.

But consider me skeptical.

The idea that this would be more efficient than combining the cold targeting ad sets into one is illogical. It goes against how it works now and opposes Meta’s recommendations.

In the past, it made sense to split out ad sets for different cold targeting segments. Not only were there more interests and behaviors to choose from, but you could have very distinct groups of people. The overlap could have been controlled.

But that’s not the case now. If you’re using Advantage+ Audience (and that’s what Meta recommends), your inputs are only suggestions. If you’re using the original audience options with interests and lookalike audiences, those audiences are expanded.

There may be initial differences in performance between your ad sets in the beginning. Some of it will be based on your inputs and some will be due to randomness. But if they’re all optimized the same way and run the same ads, the differences will eventually be minimal. The algorithm will expand to show to people most likely to convert.

That overlap is not beneficial. You’re undoubtedly getting flooded with recommendations about auction overlap and audience fragmentation with suggestions to combine your ad sets. You’re willfully ignoring those warnings.

In most cases, you should use one ad set per campaign for cold targeting. If you need further evidence that this is where things are headed, look to Advantage+ Shopping Campaigns. You can’t even create a second ad set in that case.

And an educated guess would be that the future of campaign creation will look like Advantage+ Shopping Campaigns. You can fight it with your multiple ad sets all you want for now, but it very well won’t be possible at some point.

Watch Video

I recorded a video about this, too. Watch it below…

Your Turn

What common targeting mistakes do you see?

Let me know in the comments below!

The post 6 Targeting Mistakes Advertisers Make appeared first on Jon Loomer Digital.

We’re moving into a new era of Meta advertising. Meta wants us to go broader with our targeting, and in some cases there is evidence that it’s effective. But there are times when broad targeting is bound to fail.

You may even get results that appear to be positive. But that’s part of the issue here. The performance fails once you scratch below the surface.

In this post, I want to highlight some specific situations when this is bound to happen. At the end, I’ll lay out a way that I’m trying to counter this. But ultimately, it would be helpful if Meta would come up with a way that wouldn’t require creative solutions.

What is Broad Targeting?

There’s often confusion regarding what I mean when broad targeting is discussed, so let’s define it.

When “broad targeting” is mentioned, I mean one of three things:

1. All targeting inputs are removed.

This could be because you’re using the original audience options and don’t provide anything for custom audiences or detailed targeting (only using geographic and demographic targeting). It could also be because you’re running an Advantage+ Shopping Campaign.

2. Targeting expansion is on.

You’re using the original audience options and provide custom audience, lookalike audience, or detailed targeting inputs, and you either manually turn on one of the Advantage audience expansion tools (Advantage Detailed Targeting, Advantage Lookalike, Advantage Custom Audience) or they are automatically turned on due to objective. As a result, your audience will be expanded to reach people beyond your inputs if it will lead to more or better results.

3. You’re using Advantage+ Audience.

This is now the default option when setting targeting in manual campaigns, though you can currently switch back to the original audience options. When using Advantage+ Audience, your targeting inputs (which are optional) are used only as targeting suggestions. The algorithm can then go much broader.

Optimization is Literal

This is going to come up repeatedly, so let’s address it now. It’s important that you understand that Meta ads optimization is literal. This is both a benefit and a weakness. Here’s what I mean…

Ad delivery is driven by your performance goal. The algorithm’s focus will be on getting you as many of the actions you want within your budget.

Meta will optimize and make adjustments (including who sees your ad, which will be important) based on satisfying that goal. Whether you want conversions, link clicks, impressions, or something else, Meta’s focus will be on helping you get as many of that thing as possible because that is how you’ve defined success.

That’s a benefit if all you really want is the thing that you’re optimizing for. It’s a weakness if you expect people who perform your optimization event to also perform other actions. You expect, for example, people who click a link to land on your website then behave like a normal human who may do other things.

But the algorithm doesn’t care about those other actions. It only cares about satisfying that initial goal.

When Broad Targeting Works

Broad targeting is most effective when both of the following are true:

1. Your performance goal is Conversions (number or value) and the conversion event is Purchases.

2. Your budget is high enough to generate the volume required for Meta to learn and properly optimize.

The reason this is the ideal situation is that, first, optimization is literal. Meta’s only focus is getting you purchases. When your audience is expanded, the algorithm won’t go after people likely to result in accidental or low-quality purchases. That’s just not a wide-spread and predictable issue.

Going broad is beneficial here because your results are often limited by your audience size. You add those limitations and they can restrict the algorithm from finding you more results. Additionally, that tighter audience can drive up frequency, creative fatigue, and ad costs.

A high enough budget to generate volume is helpful to get great results, but it’s not required. Let’s not get bogged down in what “high enough” means. The bottom line is that the algorithm can better learn when there’s volume of data to learn from.

Optimizing for purchases is when broad targeting is at its best. A notch below would be any other type of conversion. It’s not on par with purchases because the quality of that conversion can be an issue when the algorithm expands your audience and goes for anyone within the targeting pool.

That is also because optimization is literal. You want leads? The algorithm will get you leads. Unless you optimize for conversion leads, the algorithm does not care what those people do after subscribing.

This could potentially be controlled with tighter targeting. But once you allow Meta to target anyone beyond your target group, the characteristics of your ideal audience mean close to nothing.

When Broad Targeting Fails

Broad targeting can be an unmitigated disaster when optimizing for any top-of-the-funnel action. The problem is that, more than likely, you’ll be able to generate what appear to be great results. Meta will think they’re great results, too. But they’re likely low quality.

The reason, again, is that optimization is literal.

This is why most experienced advertisers would tell you it’s almost always a waste of money to optimize for link clicks or landing page views. The algorithm will do everything it can to get you those clicks at the lowest cost. And they could come from people who click everything (for no known reason), accidental clicks, and even bots or click fraud before they are detected.

Low-quality results are already an issue with top-of-the-funnel optimization prior to broad targeting. But if you can at least define your audience succinctly, you may be able to place some guardrails on the algorithm. You’d likely still run into quality concerns, but that will definitely be an issue if Meta can remove those guardrails and target whomever they want.

If you say you want link clicks and can’t place limited restrictions on whom you want to reach, Meta will find link clicks. You may luck out and get a few quality clicks, but most are likely to be a waste of money.

It seems as though Meta knows this because the only time detailed targeting and lookalike audiences are automatically expanded using the original audiences is when optimizing for conversions. You can turn this off when running top-of-the-funnel optimization.

Interesting, isn’t it?

An Approach to Solving Broad Targeting Issues

Let’s try to find a creative solution to this problem of quality when optimizing for top-of-the-funnel actions while going broad. Because if we did, the algorithm could actually benefit us by helping to find lower cost (and hopefully higher quality) actions.

Let’s use the example of link clicks and landing page views to drive traffic. We need an alternative when we have content that we want people to consume — and not another immediate bottom-of-the-funnel action would be expected.

This is my life, actually. My blog is important, and I do still want to drive traffic to it. We’ll want to optimize for some type of conversion, but a purchase or even lead won’t happen at a high enough rate as a direct result of reading my blog post to make that optimization realistic — without needing to spend quite a bit to get it.

You may already know that I have a large slate of custom events that fire on my website that represent some of the quality actions that I want.

Here are examples:

• Timer Events that fire at 15 seconds, 1 minute, 2 minutes, and 3 minutes
• Scroll Depth event that fires at 50% scroll
• Item in View event fires when someone views the comments
• Video Viewed event fires when someone plays an embedded YouTube video
• Click event fires when someone clicks my bot or a share button
• Internal Link Click event fires when someone clicks any link that takes them to another page of my website

These events are helpful for both optimization and reporting. To optimize for one of these events, we’ll need to create an Engagement campaign that uses the Website conversion location and Conversions performance goal.

But, which event should be the optimization event? This may not sound like an important question, but I’ve found some of the same issues with my custom events when it comes to the algorithm being literal. If I optimize for a timer event, I’ll end up with people spending lots of time on the page, but they never do anything else. If I optimize for scroll, they’ll scroll, but immediately abandon.

We also need to consider costs and volume. If it ends up costing $10 for one of these events as the central conversion event, I’ll need to spend $500 per week just to exit the learning phase for what is essentially a traffic campaign.

Here’s an example of what I’m experimenting with now, but I may still make adjustments…

I’m running ads that send people to one of my short-form video custom post types. Because of that, the YouTube video is embedded at the top of the post and there’s a short blog post below it.

For now, I’ve chosen to set the central conversion event as VideoWatched, which is the event that fires when someone starts the embedded YouTube video.

When optimizing for such an event that can happen over and over, a critical element is the Attribution Setting. Make sure it’s 1-day click only, otherwise the results will be inflated.

I’m using Advantage+ Audience, but with targeting suggestions of people who have fired the VideoWatched event during the past 180 days or those who are in the top 25% of time spent on my website. I’m hoping this initial group will provide the actions I want to give the algorithm something to learn from prior to going broader.

I’m also excluding anyone who viewed one of seven different posts for at least 15 seconds I’m going to promote in this campaign. This will also prevent unnecessary frequency.

I’ve created multiple ads for different video posts, hoping to give the algorithm something that will work. Since I already post Reels, people are accustomed to seeing these in the feed. So I use link ads that use the featured image of these videos, making it clear that they will be watching.

So far, the results have been solid. A reasonably high percentage of the people who click are spending at least 15 seconds (or a minute), scrolling, clicking internal links, and watching the embedded video. This isn’t shocking because I’ve experimented with this approach before. The caveat here is that we’re trying to make it work with broad targeting.

It’s early, but the Video Watched event volume is still the lowest of those custom events, so I may make an eventual adjustment and optimize for something else, like internal link clicks.

What Meta Could Do Instead

Coming up with creative solutions is fun, but it’s aggravating that this is necessary. Top-of-the-funnel optimization is already problematic, but if Meta’s going to encourage or virtually force broad targeting via Advantage+ Audience, it’s practically burning money.

Meta could fix this by solving the quality issue. The custom event approach may not be as useful as it could be because the learning is isolated to my website. Why can’t Meta create standard events that represent some of this quality engagement so that there is more data?

Meta could add a Quality element to Traffic campaigns (or other top-of-funnel objectives). Do you want the algorithm to focus on the most link clicks or landing page views? Or do you want the highest quality traffic (people who are more likely to spend more time, click around, and return later), knowing that it will cost more?

This has long been a complaint, but it becomes a bigger problem if you can’t put guardrails on targeting. Whether it’s traffic or some other type of engagement, the algorithm — given a huge pool to go after — will find weaknesses to get you the most results possible. And those results will often be low quality.

Watch Video

I also recorded a video to walk through this. Watch it below…

Your Turn

How do you approach broad targeting?

Let me know in the comments below!

The post When Broad Targeting Fails appeared first on Jon Loomer Digital.

Meta advertising is nothing like it once was. The role of the advertiser has changed. New tools and features have emerged. The strategies have evolved. And if you approach targeting now like it’s 2018, you’re going to struggle.

Unfortunately, that’s exactly what we see. Some advertisers have embraced this brave new world. Others are resistant to it and insist on forcing their old strategies like a square peg in a round hole.

It’s time to wake up. In this post, we’ll evaluate how targeting has changed and how you should approach it now.

Targeting Before

Back in the day, there were three distinct buckets of targeting.

1. Cold Targeting. We loved uncovering the magical combination of interests, behaviors, and lookalike audiences to bring the best results from a cold audience. We experimented with grouping interests in one ad set and lookalikes in another. Or we’d layer interests on top of lookalikes. Should you use a 1% lookalike or 5%? What about 10%? We tested and tested and found the answer.

Even location, age, and gender were important details. A part of the country isn’t leading to conversions? Exclude it. Mainly women between 25 and 34 are buying? We’ll only target them.

2. Warm Targeting. If you wanted to go after a group of people who knew who you were and were likely to convert, there were several places to start. Target your page followers, anyone who engaged with your page or posts, people on your email list, or anyone who visited your website.

This was a go-to targeting strategy.

3. Hot Targeting. These people are hot for a reason. They performed a very specific action. I created a whole strategy around it using Evergreen Campaigns. I’d push people through several stages of a campaign, showing them a different ad every few days. And it worked great!

There was a good reason to use all three approaches. It was generally seen as good practice to have multiple ad sets, if not multiple campaigns, dedicated to each audience segment.

The Evolution of Targeting

There were a couple of turning points. One was the Cambridge Analytica scandal. While it happened in and around 2015, it wasn’t revealed until 2018 and the impact to targeting would come after. One of the main lessons was to prevent bad actors from using sensitive targeting to manipulate elections.

Another turning point was iOS 14 and the movement towards greater online privacy generally. Facebook would face greater scrutiny regarding what was collected, how it was used, and giving users more control.

These combined forces led, directly or indirectly, to the removal of thousands of interests and the inability to target specific groups when a special ad category is involved. Opt-outs also cut into remarketing audiences, making them less complete and less dependable.

In the meantime, Facebook — and eventually Meta — would need to come up with solutions that would overcome these disadvantages. That led to a focus on AI, machine learning, and expanded audiences.

The move towards broad targeting began with Advantage Detailed Targeting, Advantage Lookalike, and Advantage Custom Audience. You provided targeting, but the algorithm would be able to reach people beyond that group if it would lead to more results.

The next step was Advantage+ Shopping Campaigns, which virtually eliminated targeting inputs completely. Beyond having some say over how much you’d reach current customers, the algorithm had entire countries of users to target without restrictions.

Eventually, this same approach would begin rolling out to any campaign objective in the form of Advantage+ Audience. You can provide targeting suggestions, but otherwise the algorithm will use pixel data, conversion history, and ad engagement history to build a starting audience.

How to Approach Cold Targeting

An argument can certainly be made that there’s very little reason for interests and lookalike audiences now. But even if you use them, there’s no reason to use them the way we did before.

You don’t need to obsess over which interest is most effective because, in most cases, Advantage Detailed Targeting is automatically on and can expand your audience anyway.

There’s no reason to constantly test different lookalike audiences and percentages because Advantage Lookalike is often on by default, which will expand the percentage if necessary.

The evolution towards broad and expanded audiences changes our approach, whether you like it or not.

There’s simply no reason to spend much time on testing different audiences since the algorithm can go beyond the audience you use anyway. It’s a complete waste of time to have multiple ad sets for different cold targeting approaches when the overlap is likely to be significant and audience fragmentation may result.

What should you do?

Embrace broad targeting for cold audiences. If you’re optimizing for a purchase, test Advantage+ Shopping Campaigns.

Otherwise, use Advantage+ Audience. Add some targeting suggestions if you want. But the true power will be how the algorithm learns beyond that initial group.

I wouldn’t be surprised if we eventually see the elimination of Advantage Detailed Targeting and Advantage Lookalike in favor of Advantage+ Targeting only since the functionality is similar and confusing. But otherwise, you should embrace the expansion of your audiences when given the option.

Bottom line…

1. Create fewer ad sets for the purpose of cold audience segmentation.

2. Embrace expanded audiences when given the option for cold targeting.

3. Embrace machine learning and AI for the broadest of targeting.

Is Remarketing Dead?

This is a common refrain, and it’s at least partially valid.

Generally remarketing is mostly unnecessary. What I mean by that is that it probably isn’t necessary to target the “warm” audiences we defined at the top of this post. These are the types of groups that will be built into the initial focus of broad targeting.

You could make an argument to use some of these remarketing audiences in testing. For example, target all website visitors and turn on Advantage Custom Audience. Or provide a group of custom audiences as your targeting suggestions when using Advantage+ Audience. In both cases, though, it’s a matter of using this group as a starting point with the hope that it helps the algorithm.

We’ll figure out with time whether using custom audiences in these ways was beneficial or if the algorithm would have searched the most valuable people in those groups out anyway. But for now, it doesn’t hurt to experiment with this.

Something I haven’t bought into is abandoning remarketing completely. I still subscribe to abandoned cart remarketing for simple reasons: It works, it’s inexpensive, and it’s very profitable.

If you have a small budget, the broad targeting approach isn’t likely to yield many conversions. But you can spend a very limited amount by retargeting people who abandoned cart and get results.

Maybe I’ll change my stance on this eventually. For now, I still see remarketing to the hottest of audiences makes a ton of sense.

Your Turn

How has your targeting approach evolved?

Let me know in the comments below!

The post How to Approach Meta Ads Targeting Now appeared first on Jon Loomer Digital.

If the announcements related to Meta Advantage products are any indication, the future of Meta advertising is more automation and less control. Over and over again, we’re seeing fewer options, locked-in defaults, and a required trust that the preferred settings will get you results.

Why am I concerned about this? I have a few reasons…

1. Timing

Maybe I’m crazy, but I’d feel a whole lot better about this trend if it had happened a couple of years ago. Remember a couple of years ago? Prior to new restrictions related to privacy and iOS 14+?

It was a different world then. Facebook (they were only Facebook then) had no issues with ad attribution. If anything, some wondered whether the 28-day click window captured too many conversions. The ad platform had all of the data in the world to not only give you results but measure them.

These days, though? When Facebook has less data? When targeting is worse? When results are down?

This doesn’t feel like the right time for less control and more automation. It doesn’t feel like the time to “trust the algorithm” when that algorithm has less reliable data behind it.

I get that part of this is Meta saying that since it is so much more difficult now that there are “proven ways” that are most likely to generate the best results. But… Should we trust results and optimization that are based on less complete data?

Yeah, I’m skeptical.

2. Lack of Transparency

More and more, it seems Meta simply wants advertisers to trust that something is working.

Targeting Expansion is a great example. Your audience can be expanded automatically if it may lead to better results.

We’ll never know if the audience was actually expanded. Or how much it was expanded. Or how many results you got because it was expanded. We’re just supposed to trust that it works. And we’re also seeing this with Lookalike Expansion and now a test of Custom Audience Expansion.

Without transparency and the ability to see those numbers, I don’t trust a further loss of control.

3. Apparent Desperation

The push seems to be for increasing audience sizes because that’s how you’ll get more results. Trust the algorithm because that’s how you’ll get better results.

But, results are down. Revenue is down. Meta makes less if we spend less.

We spend less when we target smaller, more relevant audiences. Telling us to go broad to help the algorithm seems to be a way to get us to spend more during a time when Meta needs more results.

Or, if you’re cynical, that could be an easy connection.

4. A Failure of Non-Conversion Optimization

Meta ads optimization is really good for e-commerce businesses. Any time you can provide a product catalog and focus on a category of products, the potential for amazing optimization is there.

But, Facebook has always ignored quality optimization for anything other than e-commerce. If you want to send quality traffic to your website or get quality engagement on your posts, good luck. You’ll always get quantity (accidental clicks, spam) over quality. Meta desperately needs optimization for content creators.

These things remain painfully weak, and putting my trust 100% into automation will only continue to provide empty numbers. You’ll get results, in the eyes of Facebook, sure. But those results will rarely be worth much (run a Traffic campaign to see what I mean).

5. It’s Nice to have the Option of Control

In the end, I’m not all that bothered by Meta moving towards optimization and streamlining campaign creation. Sure, create the supercomputer option that is fully automated. Maybe it works!

But, maybe it doesn’t work for me. I worry that this trend toward automation will eventually remove the option of control. As long as there’s an option, I can always work around that automation if it doesn’t work for me. Without the option, it becomes more and more difficult to work around the weaknesses of the algorithm.

Your Turn

What do you think about this trend towards automation? Is it a good thing?

Let me know in the comments below!

The post Reasons to Be Concerned About the Trend Toward Meta Automation appeared first on Jon Loomer Digital.

When I logged into Ads Manager recently, I noticed a new alert at the top. I had been selected for an advertising study. Based on the description, it seems Meta is testing Custom Audience Expansion.

I know that’s not the best image. And I no longer see the message. But the full alert read as follows:

This ad account has been selected to participate in a 9-week study to help improve campaign performance. A small proportion of ads using Custom Audiences will be delivered to people beyond the Custom Audience. Expanding your audience is often an effective way to improve results, but you can opt out.

Next to the message was a button to opt-out.

First: Kinda cool to be part of a study!

Second: Oh, crap. What is this?

Let’s sort it out…

A Continuation of a Trend

Custom Audience Expansion would be a continuation of a trend. First, there was Detailed Targeting Expansion (which became Advantage Detailed Targeting). Then there was Lookalike Expansion (which became Advantage Lookalikes). In each case, the approach was similar:

1. You pick an initial audience to target
2. If Facebook/Meta think you can get better results, the audience will be expanded

That is precisely what’s happening here with CUSTOM audiences now (at least that’s what this looks like). You choose a custom audience or group of custom audiences to target. But, if Meta thinks you can get more or better results by expanding outside of that custom audience, the audience will be expanded.

Lack of Transparency Regarding Reporting

One problem, which I keep making regarding expansion of detailed targeting and lookalikes, is that we just have to take Facebook’s word for it. Technically, the audience will only be expanded if and when you can get more or better results. In theory, it can only be used for your benefit.

But, there’s no way to confirm that it was helpful. There’s no break-down option to see things like:

• How much your audience was expanded
• How many conversions happened because your audience was expanded
• The overall impact of expansion on your results

Because of this, we just have to trust the expansion, and that doesn’t feel right.

The Relevant Message Problem

One of the reasons remarketing is so powerful is that you can reach people with extremely relevant messaging based on things like:

• What they bought
• What they viewed on your website
• A specific action they performed

But, the way that you target these groups is with a custom audience. So, let’s say you create an ad targeting a custom audience with a very relevant ad — an ad that would be irrelevant to anyone else. We obviously would not want to reach someone outside of the custom audience.

I understand that there may be cases when expanding a custom audience may make sense. For example, if you’re targeting your website visitors generally to promote a product and you just don’t get the volume of traffic to exit the learning phase. Some expansion could be helpful.

But not always. In the example I describe, I absolutely do not want the audience expanded. Hopefully, it won’t be on at all times with an inability to turn it off. Of course, expansion always is on in some cases related to detailed targeting and lookalike audiences, so there’s reason to be concerned.

Trust Expansion?

This test is part of a continued trend related to Meta Advantage:

• More automation
• Less control
• More trust in Facebook
• More hidden behind the curtain

While automation can be helpful, too much automation can be a problem.

Your Turn

Do you have an ad account that is part of this test? What do you think?

The post Meta is Testing Custom Audience Expansion appeared first on Jon Loomer Digital.

Meta consolidated all of its automation products under the “Meta Advantage” suite.

So, what does this mean? What’s the difference between Advantage and Advantage+? Should you care?

Let’s discuss…

The Meta Advantage Suite

The Meta Advantage suite is split into two different product lines: Advantage features and Advantage+ products.

Advantage features are focused primarily around targeting and optimization automation. Advantage+ products prioritize automating campaign creation and creative.

The benefits of Meta Advantage (according to Meta):

1. Optimization
2. Personalization
3. Efficiency

Following are the Advantage features:

• Advantage Detailed Targeting
• Advantage Lookalike
• Advantage Custom Audience
• Advantage Campaign Budget

And here is a running list of the Advantage+ products:

• Advantage+ Shopping Campaign
• Advantage+ App Campaign
• Advantage+ Placements
• Advantage+ Creative
• Advantage+ Creative for Catalog
• Advantage+ Catalog Ads
• Advantage+ International Catalog Ads

Let’s take a trip through the Advantage features and Advantage+ products.

Advantage Detailed Targeting

Advertisers can provide detailed targeting based on interests and behaviors to isolate their target audience. This is one of the oldest forms of Meta ads targeting.

Advantage Detailed Targeting gives Meta the ability to expand your Detailed Targeting inputs and reach people beyond that group if it will lead to more or better results.

In the screenshot above, an objective was used that gives advertisers the ability to turn this on and off. But in some cases, Advantage Detailed Targeting is always on and can’t be turned off.

This expansion of your audience will continue to respect location, gender, and age filters as well as exclusions.

While Meta can automatically expand your audience, that doesn’t necessarily mean that your audience will be expanded — or will be significantly. The key here is that it should only be used for your benefit.

Unfortunately, there’s currently no easy way to isolate how often your audience is expanded or how effective it is, beyond creating a split test to compare results when it is on and off.

For more information on Advantage audience expansion products, read this blog post.

Advantage Lookalike

Advantage Lookalike is an audience expansion product that works similarly to Advantage Detailed Targeting, but with a minor difference.

Many advertisers provide Lookalike Audiences for targeting to reach people who are similar to customers and those who engage with their brand. Advantage Lookalike will allow Meta to reach people beyond that group if it will lead to more and better results.

The difference here is that your audience can be expanded by reaching people within a broader lookalike percentage. You may target people who are in the top 1% of those who are similar to your customers, and Meta can expand to reach people in the top 10%.

As is the case with Advantage Detailed Targeting, Meta will continue to respect your location, age, gender, and exclusion settings. And once again, there are times based on optimization when you cannot turn this off.

As is the case with all audience expansion products, it will only be used to your benefit. But unfortunately, there’s no easy way to see how it impacted your results.

Advantage Custom Audience

Advantage Custom Audience works like Advantage Detailed Targeting, but the expansion of your audience only applies to your custom audience.

As is the case with all audience expansion tools, expansion will respect your location, gender, age, and exclusion settings and will only be used to your benefit.

One difference here is that Advantage Custom Audience is always an option. There’s not currently an objective or optimization that requires you to turn it on. This is probably a good thing as there may be examples when your messaging only applies to those in a very specific group.

Advantage Campaign Budget

When you create a new campaign, one of your options is Advantage Campaign Budget.

Here’s how it works…

This applies in cases where you have multiple ad sets. Instead of setting separate budgets for each ad set, you will set an overall budget for the campaign.

Meta will then distribute your campaign budget optimally across ad sets to get you the best results. In other words, more of your budget may be spent on a high-performing ad set and less of your budget may be spent on one that isn’t leading to conversions.

While you can establish ad set spend maximums and minimums, it’s recommended that you don’t.

Each ad set will need to utilize the same optimization and bid strategy. It’s recommended that you use ad sets with similar audience sizes or you may see that most of your budget is spent on the ad set with the larger audience.

Advantage+ Shopping Campaigns

And now the Advantage+ products…

Possibly the most popular among e-commerce advertisers is Advantage+ Shopping Campaigns.

This approach offers a streamlined way of creating a Sales campaign that leverages machine learning to get the best results.

Presets are locked in and can’t be changed.

Targeting is broad, based only on location, allowing the algorithm to find your customers.

The advertiser provides custom audiences at the account level that define current customers…

…and can then determine a budget cap for how much of the budget is spent on current customers.

You can also set Audience Controls for Advantage+ Shopping Campaigns to prevent your ads from being shown to certain ages and in restricted locations.

Advantage+ App Campaigns

Advantage+ App Campaigns automate and streamline app install campaigns while using machine learning to deliver the best results.

As is the case with Advantage+ Shopping, the advertiser will have fewer steps and customization options, putting more faith in the algorithm. Meta suggests use this when scaling your app installs is a primary objective.

Advantage+ Placements

Advantage+ Placements was formerly known as Automatic Placements.

When you utilize Advantage+ Placements, Meta will automatically optimize what placements are used and when to get you the most results for your budget.

While advertisers have a long history of manually selecting the placements that they believe are most effective, it is often best practice to turn on Advantage+ Placements. The manual selection of placements may restrict the algorithm and force your ads to be shown in the most competitive placements, driving up your costs.

There are exceptions of course (particularly when optimizing for clicks or ThruPlay), but it usually makes sense to use Advantage+ Placements when optimizing for any type of conversion. The algorithm will optimize in real time based on the performance of each placement to get you the best results.

Advantage+ Creative

Advantage+ Creative allows Meta to automatically adjust your ad creative to get the best results.

Examples of adjustments include:

• Standard Enhancements
• Music
• 3D Animation

Standard Enhancements allow Meta to automatically make the following adjustments to your media:

• Adjusting the image brightness or contrast
• Applying artistic filters
• Varying aspect ratio
• Adding templates to a feed image

And examples of ad-level compositional changes include:

• Adding labels from your Facebook page (likes or ratings)
• Displaying relevant comments below your ad
• Swapping text combinations

When turned on, Advantage+ Creative will automatically create multiple variations of your ad, showing versions that people are most likely to respond to.

There are several possible enhancements that may be made, both to media and ad-level compositional changes. You can get a preview of what these enhancements will look like when creating your ad.

Some advertisers have complained about how some of these enhancements don’t look good or may not be consistent with branding. Make sure you take a look at how these adjustments can be applied before turning them on.

Advantage+ Catalog Ads

Advantage+ Catalog Ads have been around for a long time, but they were previously known as Dynamic Ads.

By providing a catalog of your products that includes details like product name, price, description, and image, Meta can dynamically show the right ad to the right person at the right time.

This is far more efficient for e-commerce brands with hundreds or thousands of products, rather than creating individual ads for each product.

Advantage+ Creative for Catalog

Advantage+ Creative for Catalog applies the similar adjustments to your creative that’s found in the base Advantage+ Creative product.

When turned on, Meta can dynamically make adjustments to the following:

• Format: Either the carousel or collection format will be shown.
• Description variations for carousel ads: If you add catalog details to your description (like price or shipping), Meta will show the version that is most likely to lead to results for each person.
• Media and creative options for collection ads: Meta can create auto-generated videos with products from your catalog.
• Product tags: Meta may automatically add product tags to ads that appear in Instagram Feed and Explore.

Advantage+ International Catalog Ads

Advantage+ International Catalog Ads are a variation of Advantage+ Catalog Ads for cases in which you’ve uploaded country and language feeds to your catalog.

Meta will automatically show people relevant items from your catalog with the correct information for their country or language.

Should You Trust It?

Meta Advantage and Advantage+ are mostly about automation and optimization. You can do things manually or you can put your trust in Meta’s machine learning and automated adjustments.

At the very least, you should experiment with all of these features and products, where relevant. You may have reservations, but you may be surprised by the results.

Meta Advantage has challenged many of our advertising assumptions. There was a time when it was generally considered best practice to manually select your target audience or turn certain placements off, for example. But as Meta improves its systems, we need to adjust.

There are certainly exceptions and times when it may not be best to use these options. But you should still make that determination for yourself on a case-by-case basis.

Your Turn

What do you think about Meta Advantage? Is it a good thing?

Let me know in the comments below!

The post What is Meta Advantage? appeared first on Jon Loomer Digital.

Lookalike Audiences are one of the oldest shortcuts for isolating a broad audience for targeting. Advertisers can also experiment with Facebook Lookalike Expansion to yield optimal results that scale.

Of course, this is not to be confused with Targeting Expansion, which I wrote about recently. They are similar… but different.

Let’s talk about what Lookalike Expansion is, why you might use it, and how it differs from Targeting Expansion.

What is Lookalike Expansion?

Lookalike Audiences allow you to create bigger audiences of people similar to those who are already connected to you (email list, website visitors, page engagement, and more). You can have Facebook find the people who are in anywhere from the top 1% to 10% within a country or region who are most similar to your source audience.

A question I often get is related to what percentage you should use for your Lookalike Audience. I typically tell advertisers to test and experiment. But it would seem, if it works as it should, that Lookalike Expansion will help simplify this process.

Lookalike Expansion allows Facebook to dynamically expand your audience if their system finds better performance opportunities beyond the percentage you selected.

From Facebook:

Our ad delivery system uses the Custom Audience that you based your lookalike audience on as a guide for ad delivery, while also dynamically assessing performance. If our system finds better performance opportunities beyond the percentage you selected for your lookalike audience, lookalike expansion allows us to dynamically make updates that reflect where we’re seeing better performance and we may expand your audience further to include similar opportunities.

Lookalike Expansion is automatically enabled for new, duplicated, and draft campaigns and ad sets optimizing for conversion, value, or app events using Engagement, Leads, App Promotion or Sales objectives while using conversion, value, or app event optimization. You’ll notice a checkbox after selecting a Lookalike Audience when creating such a campaign.

Note that Lookalike Expansion will not expand beyond the ages, genders, locations, or exclusions that you indicate in your targeting. Lookalike Expansion cannot be used with other objectives or with Special Ad Categories.

Compared to Targeting Expansion

Much of this may sound very similar to our discussions about Targeting Expansion. When turned on in that case, Facebook will test and monitor to determine if more or cheaper conversions can be found outside of your designated audience. If so, Facebook will dynamically expand to reach these other people. Facebook uses the targeting you select as a guide.

One way Targeting Expansion is different is that, unlike Lookalike Expansion, it is used when targeting demographics, interests, and behaviors. Facebook doesn’t come out and say this in their documentation, but this is also assumed to include custom audiences (we’ve tested to confirm).

The checkbox to turn this on is found below Detailed Targeting within the ad set.

Targeting Expansion is now on by default (and can’t be turned off) when used with certain objectives. It is off by default (but can be turned on) in other situations (other than Reach and Awareness, which are not eligible).

How to Use Lookalike Expansion

I alluded to it earlier, but there is one very clear value to this. There are limitless ways to create Lookalike Audiences. What will be the source? For which countries? What percentages will you use? It’s a lot to consider and test.

I’ve consistently used 1%, since this should be the most relevant group that is most likely to be effective. But that’s not always the case, of course. A bigger or different audience may result in lower competition and CPMs, leading to lower costs. You just never know without testing, testing, and testing some more.

If Lookalike Expansion works the way it should, I see no reason to turn it off if given the option. Start with a smaller, highly relevant Lookalike Audience. This will usually be 1%, but it could be the top 3% or 5% in smaller countries. Use that as the starting point. Then, turn on Lookalike Expansion so that Facebook can expand the audience if necessary.

The “if necessary” is the key. Assuming it works as designed, Facebook won’t necessarily expand if the audience is working as well as it can. But if Facebook’s ad delivery systems see that you can get more and cheaper conversions by expanding to a larger percentage, it will.

This would also seem to be a good way to scale an ad set — or at least maintain solid performance for a longer period of time. If frequency is increasing or you’re beginning to exhaust the highest performers within your designated Lookalike Audience, the assumption is that Facebook could expand beyond that group to maintain or improve performance.

But Does it Work?

I discussed this while talking about Targeting Expansion as well. One very big problem is that Facebook provides nothing within reporting to help you understand how well Lookalike Expansion is performing — or how much it is being applied.

For example, let’s assume you are targeting a Lookalike Audience (top 1%) and have Lookalike Expansion turned on. You’re getting great results. But was Lookalike Expansion applied? How far beyond that top 1% did Facebook go? What percentage of your results were from the originally targeted audience?

This is my big issue with both expansion products. How they work, how much they work, and how well they work are all hidden behind the Facebook Black Box. If our ad set is effective and expansion was turned on, we have no idea if it was effective BECAUSE it was turned on. And that’s not helpful for advertisers looking to get consistent results.

Is This Necessary?

I’m not suggesting that a dynamic Expansion is unnecessary. I just wonder if having both Lookalike Expansion and Targeting Expansion creates too much confusion. Why not just have Targeting Expansion? It can still function in the same ways when using Lookalike Audiences, but you won’t have a whole new box and term to confuse people.

Of course, there are some differences in how the two expansions are applied related to defaults and objectives that would need to be made uniform, but it would seem to be a good simplification for Facebook. I’m sure I’m not the only one who took some time to understand the difference between the two.

Your Turn

Have you experimented with Lookalike Expansion? What kind of results have you seen?

Let me know in the comments below!

The post How to Use Facebook Lookalike Expansion appeared first on Jon Loomer Digital.

Facebook is making a change to force advertisers to potentially target more broadly using Targeting Expansion for some situations. It’s a big change that could lead to more results (if it works the way it’s designed), but it may also upset advertisers wanting to limit targeting to a smaller group.

Note that this change is still rolling out (I don’t have it yet, but we’ve confirmed it happening for some).

Let’s dig in to explain what Targeting Expansion is and how this will impact your advertising.

What is Targeting Expansion?

After entering your target audience in an ad set, you may have seen a check a box to turn on Targeting Expansion.

When turned on, Facebook will test and monitor to determine if more or cheaper conversions can be found outside of your designated audience. If so, Facebook will dynamically expand to reach these other people. Facebook uses the demographics, interests, and behaviors you select as a guide.

Note that age, gender, location, and language settings you make will continue to apply. Additionally, Facebook will respect any exclusions you added to your targeting when expanding your audience.

Targeting Expansion is available for all objectives, other than Reach and Brand Awareness. It also cannot be used when promoting a Special Ad Category.

The Change

Okay, now let’s get to the big change.

Announced in Marketing API v12.0, Targeting Expansion will be turned on automatically when optimizing for conversions, value, or app events while using the Conversions objective.

When Targeting Expansion is turned on automatically in these cases, advertisers will not be able to turn it off. It will look like this (thanks to Luke Elliott for the image)…

Note that when optimizing for actions other than conversions, value, or app events, targeting expansion will be turned off by default — but can be turned on (other than the situations described earlier).

The Problem with Targeting Expansion

I’ll admit that I really wasn’t happy when this was first announced. I enjoy targeting a small, warm audience when trying to get conversions. It’s part of my process. But, this update has forced me to take a closer look at how Targeting Expansion works and whether it may work for me.

One of the surface-level problems with Targeting Expansion is that when you turn it on, the “Potential Audience” immediately balloons to the size it would be if you removed all targeting restrictions within a location.

Truthfully, this is what upset me. It may have been my own basic misunderstanding of how this works — or is supposed to work.

If Targeting Expansion works as it should, it isn’t always applied. It may be rarely or never applied. It’s just that Facebook COULD expand your audience as much as the delivery system wants (within constraints mentioned earlier) if it may lead to more conversions.

This, of course, is where it gets dicey. There’s a lot of “in theory” that does some heavy lifting when talking about Targeting Expansion. “In theory,” you could end up with more conversions if Facebook expands your audience. But, there’s a whole lot of “we don’t really know what happened” going on as well.

What I mean is that there is no easy way to get reporting from Facebook on if or how much Facebook applied Targeting Expansion when it’s turned on. There’s no column that shows you generated “X” additional conversions because you reached people outside of your initial target audience.

And that’s where everything falls into a black box, and we just have to trust that it’s working as it should.

Does it Work?

Historically, I haven’t had great success with Targeting Expansion. But I was inspired to try it again this week, and I am seeing better results than expected for a Lead Generation campaign (this wouldn’t be impacted by the changes to Conversions campaigns, of course).

Part of me doesn’t like being forced to turn this setting on. If I wanted to target this smaller audience, I should be allowed to!

But at the same time, “in theory,” Targeting Expansion may not even be applied. If the audience you are targeting is so great, Facebook may not need to ever apply Targeting Expansion. Or it may only use it a little. And it SHOULD lead to better results.

“In theory,” of course. And we’ll never know whether it was applied or not.

The post Facebook Targeting Expansion Becomes Default appeared first on Jon Loomer Digital.