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

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

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

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

Grid Comparison

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

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

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

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

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

Advantage+ Audience (Any Performance Goal)

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

Respected Inputs:

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

When you make customizations here, the following are respected…

Location

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

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

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

Minimum Age (18-25)

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

Note that age maximum is not an audience control option.

Excluded Custom Audiences

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

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

Languages

This control is unlikely to be used all that often.

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

Audience Suggestions:

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

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

That includes settings for:

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

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

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

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

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

Original Audiences (Conversions Performance Goal)

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

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

Respected Inputs:

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

Audience Expanded:

• Lookalike Audiences
• Detailed Targeting

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

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

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

It Depends:

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

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

Original Audiences (Link Clicks/Landing Page Views)

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

Respected Inputs:

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

Audience Expanded:

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

This was a change that rolled out in early 2024.

It Depends:

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

Original Audiences (Any Other Performance Goal)

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

Respected Inputs:

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

Audience Expanded:

Nothing is expanded by default.

It Depends:

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

Advantage Custom Audience and Advantage Lookalike are both optional.

What Should You Do?

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

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

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

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

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

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

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

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

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

3. When Using Any Other Performance Goal

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

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

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

Your Turn

How do you approach audience inputs and expansion?

Let me know in the comments below!

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

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

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

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

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

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

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

Let’s get to it…

Test 1: How Much Do Audiences Expand?

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

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

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

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

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

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

The Test

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

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

• Engaged Audience
• Existing Customers
• New Audience

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

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

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

The Results

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

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

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

What I Learned

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

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

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

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

Read More

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

How Much Do Audiences Expand Using Advantage Custom Audience?

Test 2: How Much Remarketing Happens When Going Broad?

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

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

The Test

I created a campaign with the following settings…

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

The Results

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

And yet…

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

What I Learned

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

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

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

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

Read More

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

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

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

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

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

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

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

The Test

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

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

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

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

But, that didn’t play out…

The Results

Once again, quite shocking.

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

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

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

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

What I Learned

Every test surprised me. This one shook me.

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

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

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

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

Read More

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

Audience Suggestions May Not Always Be Necessary

Test 4: Comparing Performance and Quality of Results

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

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

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

The Test

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

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

The three ad sets took three different approaches to targeting:

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

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

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

The Results

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

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

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

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

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

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

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

What I Learned

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

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

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

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

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

Read More

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

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

Test 5: Understanding the Contribution of Randomness to Results

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

That got me thinking about randomness…

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

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

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

The Test

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

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

The Results

Wow. Yes, there was a noticeable difference.

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

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

What I Learned

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

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

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

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

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

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

Read More

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

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

My Approach Now

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

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

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

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

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

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

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

Run Your Own Tests

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

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

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

Replicate what I did. Then report back!

Your Turn

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

Let me know in the comments below!

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

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

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

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

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

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

2. Manual campaign with a custom audience exclusion.

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

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

If using original audiences, you can exclude custom audiences.

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

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

1. Completeness and Accuracy of Data Provided

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

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

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

To troubleshoot, ask yourself these questions…

Do your excluded custom audiences actually include existing customers?

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

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

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

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

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

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

That will create holes in your exclusions.

2. Meta’s Ability to Match the Audience

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

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

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

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

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

3. Meta’s Ability to Actually Exclude Them

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

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

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

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

The Expansion Myth

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

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

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

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

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

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

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

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

One of those controls is excluded custom audiences.

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

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

Your Turn

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

Let me know in the comments below!

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

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

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

I tested using the following three targeting strategies:

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

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

Here’s what we’ll cover:

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

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

Let’s begin…

Campaign Basics

I created a campaign using the Sales objective.

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

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

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

2. Attribution Setting: 1-day click.

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

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

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

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

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

5. Placements: Advantage+ Placements.

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

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

Targeting

Each ad set utilized a different targeting approach.

1. Advantage+ Audience without suggestions.

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

2. Detailed Targeting with Advantage Detailed Targeting.

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

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

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

3. Lookalike Audiences with Advantage Lookalike.

I selected lookalike audiences based on the following sources:

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

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

A/B Test Setup

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

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

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

Surface Level Data

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

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

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

Conversion Results

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

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

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

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

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

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

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

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

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

Quality

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

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

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

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

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

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

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

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

Remarketing and Prospecting Distribution

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

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

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

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

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

Here are the breakdowns…

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

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

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

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

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

Potential Contributing Factors

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

1. The Detailed Targeting selected.

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

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

2. The Lookalike Audiences selected.

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

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

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

3. Activity and history on my account.

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

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

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

4. Industry.

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

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

5. Location.

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

6. Randomness.

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

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

What it Means

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

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

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

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

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

Test this yourself and report back.

Your Turn

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

Let me know in the comments below!

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

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

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

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

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

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

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

Interests, Behaviors, and Detailed Targeting

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

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

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

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

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

1. Inaccuracies.

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

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

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

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

2. Expansion.

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

If you optimize for conversions, link clicks, or landing page views and you provide detailed targeting inputs, Advantage Detailed Targeting is automatically turned on. It can’t be turned off.

This means that your ads will reach people beyond those interests and behaviors if it can improve results. Your audience is expanded.

We don’t know how much your audience is expanded. We don’t know how much of your budget will be spent on the interests you listed and on people beyond those groups. But, this uncertainty matters.

There’s a very wide range of possibilities here. Maybe only a small percentage of your budget is spent on reaching people beyond your intended interests. Maybe most was spent on people you didn’t plan to target.

You should have concerns regarding the accuracy of detailed targeting inputs. You should also assume that there’s a distinct possibility that the results you get have more to do with the expansion of your audience than the inputs you provided.

While we can’t say definitively that interest targeting doesn’t matter at all, the amount of positive impact they can make is certainly in question.

Bottom line: My point isn’t that you can’t get good results while using detailed targeting. A common response I get from advertisers is that they get good results when they use interests. The point is that it’s questionable how much your selections of interests and behaviors impacted your results.

Lookalike Audiences

Like interest targeting, lookalike audiences are not new. When they were announced, lookalikes presented an enhancement from using interests only. Instead of guessing about what your customer was interested in, you could have Meta find people who were most similar to your customers.

While they made sense at one time, it’s questionable whether they remain relevant today. At the very least, they’re certainly less useful than they once were.

1. Expansion.

Once again, there’s a bit of fuzziness about the parameters you’re providing. When optimizing for conversions, Advantage Lookalike is automatically turned on and it can’t be turned off.

This means that you may reach people beyond the percentage of lookalike that you selected. We won’t know how much this is expanded or how much of your budget is spent on this expansion versus your selected audience.

2. Algorithmic Targeting.

I generally find it curious that advertisers will favor lookalike audiences over Advantage+ Audience (which we’ll cover in more detail shortly). Lookalike audiences are algorithmically driven. Meta will search for people similar to those in your source audience and compile an audience that is much, much larger.

Instead of using a lookalike audience based on your current customers, let’s instead assume you use Advantage+ Audience without suggestions. By definition, Meta will use signals like pixel activity, conversion data, and prior engagement with your ads to determine who should be in your audience.

It seems odd to be okay with Meta’s development of lookalike audiences but not with algorithmic targeting. There are very obvious similarities between the two.

How much impact do the lookalike audiences that you provide have on your results? Due to expansion, we don’t know. And why should we prefer it over Meta’s more recent algorithmic targeting developments?

Targeting Inputs are Deprioritized

You may not like it, but it’s clear what Meta is doing. If you use original audiences and optimize for conversions, your detailed targeting and lookalike audiences will be expanded. Those inputs are less important than they once were.

Of course, Meta doesn’t want you to use those approaches anyway. Meta wants you to use Advantage+ Audience.

While you can provide targeting inputs, it’s pretty darn obvious that Meta doesn’t think this is necessary. Otherwise, those inputs would be immediately available.

If you provide custom audiences, lookalike audiences, detailed targeting, age maximum, or gender, they will be used as audience suggestions.

This is the default way to impact targeting. While the option to provide targeting inputs using original audiences still exists, Meta works hard to discourage you. When you click to use original audiences, you’ll get an alert asking if you’re sure.

Meta’s tests show that you can improve your results by up to 33% if you use Advantage+ Audience over original audiences. It’s in Meta’s best interests that you get those superior results.

When it comes down to it, Meta may not even prefer that you use Advantage+ Audience. When creating a sales campaign, you are defaulted to Advantage+ Shopping Campaigns.

You still have the option of creating a manual sales campaign, but Meta clearly wants you to go this route.

Advantage+ Shopping Campaigns take algorithmic targeting even further. Your targeting inputs are virtually non-existent.

It’s not that you will always get better results using Advantage+ Audience or Advantage+ Shopping Campaigns. But, Meta has found that advertisers do get better results with these methods, on average. And your impact on targeting in either case is minimal.

Remarketing

I still remember how excited I was when advertisers were given the ability to target website visitors. It changed the entire industry.

You don’t need to convince me of the value of reaching people who are deeply connected to us. I lived primarily off of remarketing for a very long time. The question is whether much of the remarketing that we once did is still necessary.

Audience Segments for sales campaigns opened my eyes to this possibility. Once you define your Engaged Audience and Existing Customers (essentially your remarketing audiences), you can see how much of your budget is spent on remarketing while not even trying.

In my tests, it doesn’t matter whether I use Advantage+ Audience (with or without suggestions) or original audiences. I regularly see a similar distribution between remarketing and prospecting.

If Meta is going to prioritize your remarketing audience anyway, why is it necessary to create separate ad sets to reach your remarketing audience — especially a general remarketing audience (all website visitors, for example)?

The primary argument for remarketing now is if you have a unique message for a very specific group of people that would only be relevant to them. Minus such a message, it just doesn’t feel necessary.

Exceptions and Caveats

I’ve been careful to specify that the situations when detailed targeting and lookalike audiences are least impactful are when those audiences are expanded. The end result is likely more like Advantage+ Audience than you think.

But, there are times when you can turn expansion off — and it may even be recommended. If your performance goal is post engagement, ThruPlay, or just about anything other than a conversion (or link clicks and landing page views for detailed targeting), Advantage Detailed Targeting and Advantage Lookalike are options that can be turned on or off.

I’m not suggesting that turning off expansion will give you better results. Instead, your inputs obviously mean more if targeting is restricted to what you provide.

There are also times when using original audiences instead of Advantage+ Audience may be preferred, especially when optimizing for top-of-the-funnel actions. Not only do you get more control over detailed targeting and lookalike audiences, but age maximums and gender become tight constraints. If you’ve seen that your budget is wasted outside of your demographic preferences when using Advantage+ Audience, this is always an option.

That said, this still doesn’t have anything to do with your detailed targeting and lookalike audience selections.

How Much Does It Matter?

If I’m successful at nothing else with this post, I hope that you at least walk away with a new skepticism about your impact on targeting.

I said it before, but it requires repeating: This isn’t about whether Advantage+ Audience is superior to using interests and lookalikes. It’s that any difference between the three approaches has the potential of being completely random.

If you’re getting great results using a certain group of interests, it may be partially due to the interests you’re using. It may be mostly due to the expanded audience. We don’t know. The main thing is that the inputs you provided aren’t likely to be the main or only reason you’re getting those results.

Results from test after test are showing me this. Surface level metrics are nearly the same. Distribution between remarketing and prospecting are nearly the same. Results are nearly the same.

And when there’s a wider difference, it’s a disparity that often can’t be replicated when I recreate the test. It was random.

That’s why I want you to obsess less over these things. It’s not that I demand you stop using original audiences with interests and lookalikes. I just want you to stop obsessing over them. It’s unlikely that you found the perfect combination of targeting inputs.

Advertisers are superstitious creatures. Even if we know that something we’re doing isn’t why we’re getting great results, we don’t want to rock the boat. And that’s perfectly fine.

But, I encourage you to resist the need to over test your targeting. If you continue to create multiple ad sets for different groups of people, hoping to isolate the best performing selection of targeting inputs, you are likely doing more harm than good.

It’s also a potentially colossal waste of time that could be better spent on things that matter, like your ad copy, creative, landing page, and attribution.

The Direction We’re Heading

This should be obvious…

1. In a very limited number of situations, you can avoid having your detailed targeting and lookalike audiences expanded. In those that remain, they may be expanded by default, but you can turn it off. Meta wants you to turn it on.

2. When optimizing for conversions (and sometimes link clicks or landing page views), your ads can be delivered to people outside of the interests and lookalikes that you provide.

3. The default approach to targeting is Advantage+ Audience. Meta doesn’t want you to use original audiences and tries to discourage you from using them.

4. Meta doesn’t even seem to care if you provide any targeting at all with Advantage+ Audience. When you do, it’s merely a suggestion.

5. If you’re creating a sales campaign, it defaults to Advantage+ Shopping, which allows for virtually no targeting inputs at all. This is what Meta wants you to do.

Your targeting inputs matter far less than they ever did before. More importantly, Meta doesn’t seem to want or even need them. And the trend line is towards eliminating them entirely.

You can be upset about this, but I simply ask that you acknowledge it. Repeat after me:

“My targeting inputs mean less than ever before. Meta doesn’t want or need my targeting inputs. One day, I will likely lose all ability to control these things.”

Once you accept it, you can prepare.

How to Impact Who Sees Your Ads

This may seem like you’re placed in a helpless situation, but you’re not. Your targeting inputs may not matter much, but you can still impact who sees your ads.

1. Performance Goal. Think about it. This might be the most impactful control of all. Whether your audience is expanded or you’re using Advantage+ Audience, the algorithm is driven by finding people who will perform the action that you want, as defined by the performance goal. This includes the conversion event that you choose when optimizing for conversions.

What you define as your goal will drastically alter who sees your ad. Meta’s focus will be on helping get you that action.

2. Ad Copy, Creative, and Offer. A common claim is that the ad does the targeting now, and I don’t know that this is literally true. I haven’t seen Meta specify that the algorithm scans your copy for keywords to determine who sees your ad. But, it’s mostly semantics.

Your initial audience is likely determined by pixel activity, conversion data, and prior engagement with your ads. After that, it learns from who performs the action that you want. So, you want your ad copy, creative, and offer to attract your ideal audience.

You don’t want to attract a general audience. You want to attract very specific people. In a sense, you want your ad to repel people who aren’t your ideal customer.

These aren’t small things. Crafting effective copy, creative, and offers isn’t easy to do. Don’t feel as though a light-touch approach to targeting is somehow the easy way out. You still have work to do.

Your Turn

What’s your approach to reaching your ideal audience? Has it evolved?

Let me know in the comments below!

The post Meta Ads Targeting and an Advertiser’s Role, Explained appeared first on Jon Loomer Digital.

Are you still running Meta ads strategies that you used years ago? Do you ignore Meta’s best practices and recommendations because you swear that they don’t work?

My view of ad strategies isn’t absolute. There isn’t one approach that will always work for everybody in all situations. If you’ve found what works for you, great. Even if it’s inconsistent with what works most often, there are exceptions.

But, you also shouldn’t do this blindly. Don’t be stubborn about it. Don’t take an approach based on gut feel, a lack of trust in automation, or because something did or didn’t work a few years ago.

If you’ve been taking the same approach for the past year or longer, it’s important that you test your assumptions about what works and what doesn’t. And when you do, make sure it’s a scientific test that will provide meaningful results.

Running these tests can only be productive. It could reinforce what you believed to be true. Or the results may make you question whether what you’re doing is actually effective. You may see an alternative approach in a new light.

My advertising approach has changed dramatically over the years. I did not immediately embrace an evolving set of best practices. I was stubborn. But, my own tests have helped me understand that I was wrong. They also helped improve my confidence in another approach.

In this post, we’ll cover a handful of old school advertising targeting strategies and how you should test them against a more modern approach. Once you’ve tested, you can decide whether your stubbornness was right all along.

Testing Basics

Before we get to the old school strategies, it’s important to provide a framework for testing.

1. Use A/B Test.

I prefer to create A/B Tests in Experiments. Create the campaigns or ad sets that you want to compare first. Then go to Experiments and click to create an A/B Test.

Select the campaigns or ad sets that you want to compare. I ask you to test ad sets in two of the three examples below. In the third, you’d compare campaigns.

2. Focus on a Single Variable.

Everything about the two campaigns or ad sets should be identical except for a single variable. Since this post is about testing targeting strategies, everything beyond targeting should be the same. Make sure that there aren’t any other variables like placements or ad copy and creative that could result in differences in performance.

3. Your Key Metric

The Key Metric is what determines which campaign or ad set “wins” in an A/B test.

Make sure that this metric isn’t frivolous. What ultimately determines which ad set was better? If your goal is sales, then the key metric should be Cost Per Purchase. Do not use secondary metrics like CTR or CPC.

If your key metric is Cost Per Lead, you may want to take steps to measure the quality of those leads. Make sure that you send these leads to different forms so that you can keep track of them in your CRM.

4. Strive for meaningful results.

Your goal isn’t to find a winner quickly, it’s to find convincing results that actually mean something. Make sure that the budget dedicated to each competing campaign or ad set, combined with the length of the test, are enough to produce the volume that you need.

The longest you can run a test is a month. This would be my preference for a test that will help define your strategy going forward. Do not end the test early if a winner is found.

If the results become more convincing with time, that’s a good thing.

1. Interests and Lookalikes

There was a time when the ability to target people by interest, behavior, or lookalike audience was revolutionary. It gave advertisers targeting control and your ads were more likely to reach a relevant audience.

That isn’t always the case now. If you use Advantage+ Audience, any inputs you provide for detailed targeting or lookalike audiences will be suggestions.

This is why many advertisers have resorted to using original audiences. Targeting inputs in that case are more than suggestions — or we assume.

But, the reality is that even when using original audiences, your targeting inputs are rarely tight constraints. If you’re optimizing for conversions, link clicks, or landing page views, Advantage Detailed Targeting is automatically on.

If you optimize for conversions, Advantage Lookalike is automatically on.

In other words, we have no idea how much your selection of those interests and lookalike audiences actually matter. And based on my tests, they matter very little — if at all.

It’s not even clear that your audience suggestions matter when using Advantage+ Audience. They may actually be a detriment. This is why I recommend testing your current strategy with interests and lookalike audiences versus Advantage+ Audience without any suggestions at all.

Compare:

• Version 1: Original Audiences using Detailed Targeting or Lookalike Audiences
• Version 2: Advantage+ Audience without Suggestions

Key Metric: Cost Per Conversion (whichever event is most relevant)

Are you actually better off using original audiences to target interests or lookalikes? Maybe. But, prove it.

2. Gender and Age Control

One of the complaints I’ve heard from advertisers about Advantage+ Audience is the lack of control over age and gender.

You are only able to provide an age minimum within Audience Controls when using Advantage+ Audience.

Any age maximum or gender inputs you provide are audience suggestions. If Meta can get you more or better results by delivering your ads outside of those ranges, it will.

As a result, advertisers who feel these inputs are critical have favored original audiences. In that case, age and gender are tight constraints that will be respected.

Let’s assume that your customer is predominantly women aged 25-49. If Advantage+ Audience works the way that it should, whether or not ads are delivered to men or people outside of those age ranges will depend upon whether you can get your optimized actions from those other groups.

I’ve seen examples where businesses that serve women used Advantage+ Audience and 99% of the budget was spent on reaching women — even though gender is only a suggestion.

The key, though, is that you should optimize for conversions for this to be effective — preferably purchases. If reaching people who fall outside of expected gender and age range won’t lead to conversions, you’ll likely spend very little there.

Can you trust Advantage+ Audience without these controls? It’s worth testing for any type of conversion, especially purchases. Leads can be problematic since it’s possible you may get cheaper and lower quality leads this way — but, it’s worth testing. Engagement optimization is likely to go off the rails using Advantage+ Audience without those controls, but top-of-the-funnel optimization is problematic at its core.

Compare:

• Version 1: Original Audiences with Age and Gender Restrictions
• Version 2: Advantage+ Audience with Age and Gender Suggestions (if at all)

Key Metric: Cost Per Conversion (whichever event is most relevant)

Is it critical that you only reach people within your preferred demographic? Is it possible that Advantage+ Audience will waste money by reaching people outside of those groups? Maybe. But, prove it.

3. Remarketing

Look, my whole thing years ago was remarketing. I was generating a high volume of daily organic traffic, and ads allowed me to leverage this with highly relevant targeting.

But, things have changed. You can still target remarketing audiences. Those groups of people are surely just as relevant as they were years ago. What changed is the cost.

Targeting small groups of people is much more expensive than targeting large groups. Even though your website visitors may be three times more likely to convert, it may cost three (or five or 10) times more to reach them.

The other development is that Meta’s ad delivery algorithm has improved. Even if you use Advantage+ Audience without suggestions or go broad with original audiences, the algorithm will almost always prioritize a percentage of your budget to remarketing. We now know this due to Audience Segments.

When running Advantage+ Shopping Campaigns (or any Sales campaigns, if you have the update), you can breakdown your results by Audience Segments. I’ve often seen that between 25 and 35% of my budget is spent on people who have engaged with me (visited my website or subscribed to my email list) or bought from me.

Many advertisers continue to create campaigns with separate ad sets for prospecting and remarketing. But, since these two things happen at once without us even realizing it, is it still necessary?

For this test, we’ll need to compare campaigns since the old school approach is to use two ad sets. I would also use an attribution setting that is click only to prevent the remarketing ad set from inflating results with view-through conversions.

Also make sure that the combined budget of each campaign is the same. In other words, Version 2 using Advantage+ Audience should be the same as the sum of the two ad sets in Version 1.

Compare:

• Version 1: Campaign with Remarketing and Prospecting Ad Sets
• Version 2: Campaign with one Ad Set using Advantage+ Audience

Key Metric: Cost Per Conversion (whichever event is most relevant)

In addition to comparing the Cost Per Conversion, use your Breakdown by Audience Segments to see how your spend and results from remarketing compare.

Test Your Assumptions

I want you to test these because what I’ve seen from my own tests is quite clear. I’ve seen that…

1. Detailed targeting and lookalike audiences are rarely beneficial. Advantage+ Audience almost always gives me the same or better results.

2. Gender and age restrictions are rarely necessary. Especially when optimizing for purchases, the algorithm figures it out.

3. Remarketing is not the advantage it once was. It’s expensive to run stand-alone remarketing ad sets. Remarketing and prospecting happen together in the most optimal way now.

There are always exceptions, and I’ve even mentioned some of those cases in this post. But, if you are still utilizing some of these old school targeting strategies, I encourage you to run these tests yourself and allow for the possibility that more modern approaches may be more beneficial.

Your Turn

These are the types of tests that I often run to challenge my own assumptions. Once you’ve run these tests, I’d love to see your results.

Let me know in the comments below!

The post How to Test Meta Advertising Targeting Strategies appeared first on Jon Loomer Digital.

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.

The process of Meta ad targeting and audience selection has evolved significantly during the past few years. Advertisers have been pulled through audience expansion and into complete algorithmic targeting, largely against their will.

But, there are very good reasons why these changes, which come at the expense of advertiser control, were necessary. It started with regulatory pressure on Meta related to the misuse of targeting distinct groups in order to manipulate elections or discriminate. You could also point to a loss of reliable data due to changes in allowable tracking used for targeting.

And finally, there’s a matter of Meta’s own investment in AI and machine learning. There are times when Meta may be better at finding your ideal audience automatically than you could be manually.

These days, we’re given options. Advantage+ Audience is the default method for audience selection, but you are able to switch to Original Audiences.

Not without repeated warnings, of course…

It would be a lot easier if I could tell you to either always use Advantage+ Audience or always avoid it. It’s not that simple.

There are times when Advantage+ Audience makes the most sense. There are times when it’s probably a bad idea. But, most advertisers misunderstand when to take each approach.

It’s understandable why there’s so much confusion. Several variables apply. While Advantage+ Audience is rather straightforward, Original Audiences behave differently depending on your performance goal.

Once you better understand how each of these work, the strengths and weaknesses will begin to clarify. By the end of this post, I hope that you’ll have a better plan for when you should use Advantage+ Audience and when you should revert to the old ways.

How Advantage+ Audience Works

For each approach, let’s focus on what you can restrict, the inputs you can provide, and when Meta can expand targeting beyond your initial inputs.

Restrictions:

Audience Controls provide limited restrictions regarding who can see your ads.

Your ads will not be shown to people outside of your selected locations, minimum age, languages, or excluded custom audiences.

Note that there is not an Audience Control for maximum age or gender. Your ads will be shown to anyone who is likely to perform your goal action.

Your Inputs:

Your inputs are Audience Suggestions and they are not required. Suggestions can include custom audiences, lookalike audiences, age range, gender, and detailed targeting.

Note that these are all suggestions and not restrictive. Ads can be shown to people outside of your selected custom audiences, age range (assuming it’s within the age minimum Audience Control), gender, and detailed targeting.

If you don’t provide suggestions, Meta will begin with your pixel data, conversion history, and prior engagement with your ads while searching for people most likely to perform your goal action.

Expansion:

I don’t know if defining what Meta does here as “expansion” is accurate, but it’s a way to compare Advantage+ Audience with what can happen using Original Audiences.

Meta will initially prioritize your audience suggestions before going much broader. Ultimately, the algorithm will show your ad to anyone (assuming this is allowed by Audience Controls) if they are likely to lead to more of the action you want, as defined by the performance goal.

How Original Audiences Work

Original Audiences allow you to use targeting the way you “used to” use it — but not the way you did it several years ago. It just provides more control than Advantage+ Audience, though there are several variables that alter how it works.

Restrictions:

Meta will not deliver your ads to people outside of your selected locations, age range, gender, exclusions (custom audience or detailed targeting), or languages.

There are signs that detailed targeting exclusions may be going away, but Meta is currently saying that there are no immediate plans for such a change.

Your Inputs:

In addition to the audience inputs listed above in Restrictions, advertisers can provide custom audiences, lookalike audiences, and detailed targeting.

Expansion:

This gets somewhat complicated with Original Audiences. In some cases, Meta can serve your ads beyond your selected detailed targeting or lookalike audiences, and you can’t turn it off. Sometimes you have the option. And whether or not you have an option may be different, depending on your version of Ads Manager.

Advantage Custom Audience: When you provide a custom audience or group of custom audiences, you have the option to turn on Advantage Custom Audience. When on, your ads can be delivered to people beyond your selected custom audiences if it will lead to better results.

There is always an option to turn Advantage Custom Audience off when using Original Audiences, regardless of the performance goal.

Advantage Lookalike: Lookalike audiences allow you to create a pool of people who are similar to those who are connected to you in some way. When creating these lookalike audiences, you can focus on those who are within the top 1 to 10% of those most similar within a given country or group of countries.

When you provide a lookalike audience for targeting, Advantage Lookalike allows Meta to show your ads to people outside of your selected percentage if it will improve performance.

This cannot be turned off when optimizing for conversions.

Advantage Detailed Targeting: Advertisers can target people based on interests and behaviors on and off of the Meta family of apps using detailed targeting. Advantage Detailed Targeting allows Meta to reach people beyond those inputs if it will improve performance.

Similar to Advantage Lookalike, Advantage Detailed Targeting is on by default and cannot be turned off when optimizing for conversions.

While it appears to be Meta’s plan to make this the default when optimizing for link clicks and landing page views, it’s not currently the case for all advertisers.

A Summary of Control

There are multiple reasons to favor one approach over the other. For many advertisers, it’s a matter of control, even though that complaint isn’t always justified as a harm.

Let’s summarize the level of control for each approach…

Advantage+ Audience

Controlled:

• Locations
• Minimum Age
• Languages
• Excluded Custom Audiences

Audience Suggestions:

• Custom audiences
• Lookalike audiences
• Age range
• Gender
• Detailed targeting

Original Audiences

Controlled:

• Locations
• Age Range
• Gender
• Languages
• Excluded custom audiences

Optional Expansion:

• Advantage Custom Audience
• Advantage Detailed Targeting (all but for conversions, link clicks, and landing page views)
• Advantage Lookalike (all but for conversions)

Forced Expansion:

• Advantage Detailed Targeting (for conversions, link clicks, and landing page views)
• Advantage Lookalike (for conversions)

As a reminder, not all versions of Ads Manager have forced audience expansion when optimizing for link clicks and landing page views, but Meta announced this as a change.

When to Use Advantage+ Audience

Advantage+ Audience leverages algorithmic targeting, putting minimal limits on whom can be reached in an effort to get you the most desired actions at the lowest cost.

The assertion that Advantage+ Audience leads to lower costs is difficult to dispute (or prove false). The question is related to quality.

When you should use Advantage+ Audience can be summarized like this…

1. When optimizing for purchases. You could make the argument that you should instead use Advantage+ Shopping Campaigns, but Advantage+ Audience is a good option as well. The algorithm can’t be misled by low-quality purchases, since this isn’t a thing. It will do what it can to get you the most purchases at the lowest cost. If you desire higher value, you can optimize for Value instead.

2. When optimizing for other types of conversions. There is a caveat here since quality is something to monitor. But, I’ve found Advantage+ Audience to be plenty effective for running lead campaigns. When quality is a concern, you can also assess your lead forms or optimize for Conversion Leads instead.

When to Use Original Audiences

Choosing to use Original Audiences is less about leveraging a unique strength of this approach and more about avoiding a potential weakness associated with Advantage+ Audience. But, let’s be clear: Original Audiences merely help limit the issues associated with certain types of optimization.

1. Top of Funnel Optimization. Whenever possible, you should select a performance goal that is near the bottom of the funnel (conversions or leads). The algorithm’s focus is getting you as many of those actions as possible. But, if you optimize for link clicks, landing page views, post engagement, ThruPlay, or some other type of top of funnel action (and you have no choice), you should use Original Audiences.

Top of funnel optimization is already problematic because the algorithm does not care about generating quality link clicks, landing page views, post engagement, or ThruPlays. Its only focus is getting you that thing, regardless of who is performing the action. This is why Advantage+ Audience can make what is already a problem even worse.

Original Audiences allow you to put some guardrails on your targeting. You can isolate gender, age ranges, and even lookalike audiences and detailed targeting. Of course, if you have the update that forces audience expansion for link click and landing page view optimization, it’s less restrictive.

Keep in mind that having customers who are primarily a certain gender or within a specific age group isn’t enough to require Original Audiences. If you optimize for purchases, use Advantage+ Audience — the algorithm will focus on those most likely to purchase. But, this customer focus is more reason to switch to Original Audiences for the top of the funnel (though you should have made that switch anyway).

2. Remarketing. If you want to run ads that only reach people within a custom audience, Advantage+ Audience is not the method for you. The custom audience you provide will only be used as an audience suggestion. You should instead use Original Audiences.

The question is whether you need to run a “true” remarketing campaign. Some advertisers run general remarketing campaigns to their email list, website visitors, or people who engage with their ads because they assume these people are more likely to act on their ads. If that’s the case (and you’re optimizing for conversions), I still recommend using Advantage+ Audience and listing custom audiences as suggestions.

The only time when using Original Audiences for remarketing would be necessary is if you have a unique message that only people in that audience should see. Original Audiences will allow you to isolate that group.

Have a Reasoned Approach

I hope this post provides some clarity on how these two approaches work and when you might use both. Find what works for you. But, I ask that you make sure that your reasons for doing what you do are backed in facts and not assumptions.

If you assume that your targeting inputs are critical to the performance of your ads, you will likely prefer using Original Audiences in most cases. But, I encourage you to challenge that assumption. Experiment more thoroughly with Advantage+ Audience. Remember that your audiences are often expanded anyway when using Original Audiences.

Make sure that your reasoning for abandoning Advantage+ Audience is backed by a known weakness. If you primarily serve women, do not assume that if you optimize for purchases and use Advantage+ Audience that your ads will be shown to men. More than likely, it will be the opposite.

Your Turn

How do you approach when to use Advantage+ Audience or Original Audiences?

Let me know in the comments below!

The post Advantage+ Audience vs. Original Audiences appeared first on Jon Loomer Digital.

Meta has begun to roll out an update to ad sets utilizing performance goals for link clicks and landing page views, which was originally announced in January. When using original audiences, Advantage Detailed Targeting is automatically applied.

If you missed that Advantage Detailed Targeting was turned on, you’d be forgiven. This design variation is not at all obvious. If you miss the new label, you won’t see that the audience may expand unless you hover over one of the tooltips.

This is a departure from the primary design I’ve seen when using conversion performance goals. In those cases, a message is highlighted in gray.

But, let’s back up. There’s plenty to unpack here. The signs are all around us that we’re headed towards a future of less targeting control, regardless of the performance goal. And that could be a problem, unless Meta makes some much-needed improvements.

In this post, let’s discuss:

• The current state of audience expansion
• Where expansion is effective
• Where expansion fails
• Where this is headed
• What Meta needs to do

At the bottom of this post, I’ve also recorded a video that summarizes what is going on.

Current State of Audience Expansion

Meta first unveiled audience expansion in 2021 with a suite of products that would eventually fall under the “Advantage” line. Here is how they work…

Advantage Detailed Targeting

Advertisers provide detailed targeting inputs that Meta prioritizes. Your audience can be expanded to reach people beyond that group if better results can be found.

Not long after its initial rollout, Advantage Detailed Targeting became a fixed default for any conversion-related performance goal. Otherwise, advertisers had the option of turning it on or off.

That, of course, changed with this latest rollout of Advantage Detailed Targeting for ad sets utilizing link clicks or landing page views performance goals.

Advantage Lookalike

The second of the Advantage expansion family, Advantage Lookalike works in a similar manner as Advantage Detailed Targeting. If Meta detects that better results can be found beyond the selected percentage of your lookalike audience, the percentage can be expanded.

For example, if you use a 1% lookalike, the audience could be expanded to anywhere from 2 to 10%.

Like Advantage Detailed Targeting, Advantage Lookalike is turned on by default for conversion performance goals and cannot be turned off.

The latest update to link click and landing page view performance goals has not been applied to lookalike audiences. Advertisers still have the option of turning this on or off in that case (for now).

Advantage Custom Audience

Next, Meta rolled out the ability to expand custom audiences if better results can be found. Unlike the first two features, there is always an option to turn Advantage Custom Audience on or off. There isn’t currently a case where it’s on by default (though this may change).

Of course, Meta then took things even further…

Advantage+ Audience

Beginning in August of 2023, Advantage+ Audience became the default way of selecting an audience in the ad set. Advertisers still have the ability to switch back to original audiences, where the three Advantage expansion tools may be applied.

When using Advantage+ Audience, any targeting inputs provided are seen as mere suggestions. You will reach people beyond that initial group, and providing suggestions is optional. If you don’t provide them, Meta will automatically begin with your pixel data, conversion history, and prior engagement with ads as a guide.

Advantage+ Audience is the initial default for all campaign objectives, regardless of the performance goal. When used, any targeting inputs — custom audiences, lookalike audiences, detailed targeting, and even gender and age maximum — are seen as audience suggestions, and your ads may reach people beyond those groups.

Where Expansion is Effective

While I initially resisted audience expansion (“I only want to reach the people I’m targeting!”), I’ve come around to it. But, it’s most effective for a unique set of circumstances.

Audience expansion (any of the Advantage expansion tools or Advantage+ Audience) can work because the algorithm is hyper-focused on finding your desired action, as defined by the performance goal. Your targeting constraints could conceivably restrict the algorithm from getting more of those actions.

This is especially true when optimizing for purchases.

Success is defined by getting more purchases within your budget. If your targeting can be expanded to find more purchases, that’s a good thing.

There’s no better example of this in action than Advantage+ Shopping Campaigns. Targeting inputs are virtually nonexistent, and yet Meta says that they lead to a 17% improvement in cost per acquisition and a 32% increase in return on ad spend.

Where Expansion Fails

For the same reason that audience expansion can be effective for purchase optimization, it often fails for anything else — especially when using a performance goal that represents a top-of-the-funnel action (link clicks, landing page views, ThruPlay, post engagement, and more).

The audience will expand beyond your inputs if more of the actions defined by the performance goal can be found.

This isn’t a problem when optimizing for purchases because getting the purchase is the ultimate determinant of success. The algorithm makes adjustments based on whether it can get you more purchases.

It’s a problem for everything else because quality then matters…

Your audience is expanded to get more link clicks or landing page views. But did these people do anything else after clicking? Were they bots? Where they accidental clicks? Were they people who click everything? The algorithm doesn’t care.

Your audience is expanded to get more people to engage with your post. But is this positive or negative engagement? Do they fit your typical customer profile? Is there any chance that they’d ever buy from you? The algorithm doesn’t care.

Your audience is expanded to get more leads. But were the email addresses provided valid? Are these people reachable? Will they open their messages and engage? Is there any chance they’d ever buy from you? The algorithm doesn’t care (unless you optimize for conversion leads, which isn’t reasonable for everyone).

In each case, you care. And that’s the problem. Audience expansion fails when there’s no control for quality. Your targeting inputs were the only remaining constraints to focus only on potential customers.

Where This is Headed

Look to the most recent developments to predict where this is heading…

1. Advantage+ Shopping Campaigns don’t allow for any targeting inputs.

2. Advantage+ Audience is now the default, and you’re discouraged from switching to original audiences.

3. Advantage Detailed Targeting is now on and can’t be turned off when using link click and landing page view performance goals.

Every new update puts less importance on your targeting inputs. More ways to expand the audience. Fewer controls to be able to target an exact group.

Given that Advantage+ Audience is the default for all objectives and performance goals now, I’m actually surprised that Meta would make this update to Advantage Detailed Targeting related to link clicks and landing page views.

My assumption is that the ability to switch back to original audiences (and utilize Advantage Detailed Targeting, Advantage Lookalike, and Advantage Custom Audience) will eventually be eliminated. But, maybe this is a sign that such a move is further off in the future than I expect.

The bottom line is that Meta isn’t going to stop expanding audiences beyond your targeting inputs any time soon. We’re likely to see this forced for more objectives and performance goals in the future, even if you’ll be able to continue switching back to original audiences.

What Meta Needs to Do

I am not a fan of this latest update to Advantage Detailed Targeting. The reason can be found within the section about when audience expansion fails.

Optimizing for top-of-funnel actions is already problematic. But if Meta removes or de-emphasizes targeting constraints, we lose all checks on quality. It no longer matters who these people are. Meta only cares that they’ll perform the action that we want.

The solution isn’t that complicated, and it’s been needed for years. The evolution of audience expansion only makes it more imperative that Meta act on it.

There must be a way to optimize for quality top-of-funnel actions.

I’d be much more willing to use the link click or landing page view performance goals to promote my blog posts if I could require the algorithm to optimize for quality traffic — not just any traffic. This could be defined by time spent on the website, scroll depth, other conversions, and return visits.

I’d be much more willing to use performance goals related to post engagement if I could require the algorithm to optimize for quality engagement — not just any engagement. I want people who are likely to share my posts, provide thoughtful comments, and return to my content later.

This “quality” element could be an option when setting a performance goal. Do you care more about getting a high volume of actions? Leave it at the default. Do you care about quality? Check this box and expect to spend more.

If that were possible, the expansion of your audience becomes less problematic. The algorithm would expand to get more of the quality actions that you are wanting — and that is ultimately what would guide ad delivery.

This would seem like a natural solution that is good for everyone. Most importantly, advertisers would be willing to spend much more on actions other than conversions if there were an increased confidence in the quality.

Watch Video

I recorded a video about this, too, and you can watch it below…

Your Turn

Do you run ad sets optimized for link clicks and landing page views? What do you think about this update?

Let me know in the comments below!

The post Meta is Forcing Expanded Audiences for Top of Funnel Optimization appeared first on Jon Loomer Digital.

Meta announced that more detailed targeting options will be removed on January 15th. It’s the continuation of a trend that began more than three years ago.

Don’t say that I didn’t warn you.

This is a reminder that you cannot rely heavily on granular targeting. Not only might it go away, but your targeting inputs matter less and less with each new update.

I didn’t write this post to scare you. Instead, I’m hoping to break through to help you understand what’s happening and is bound to happen. It’s time to embrace this direction and prepare for it.

Targeting Trends

It’s debatable when the first shoe dropped related to the current direction of targeting. From about 2012-15, the focus was on developing new powerfully specific ways to target people. New detailed targeting to reach people by actions and behaviors. New custom audiences to reach those who have engaged with you. All focused on your inputs.

Maybe things didn’t officially start shifting during the election season of 2015, but that’s certainly when the seeds of change were planted. The use of targeting to manipulate elections attracted scrutiny. Meta (then Facebook) found itself under significant regulatory pressure.

Cambridge Analytica surely contributed to greater awareness of ways people were being tracked and how it was used for targeted advertising. Meta developed new rules for special ad categories that were aimed at preventing discrimination in the areas of employment, credit, and real estate.

Then iOS 14 happened a few years later, and doubts emerged around how accurate and complete some of our ad targeting was. Meta took an interest in machine learning, AI, and modeling to help repair lost data and fill in the gaps.

Meta performed a sweep to remove certain ad targeting options in the early parts of 2022. Those removals focused on “detailed targeting options that relate to topics people may perceive as sensitive, such as options referencing causes, organizations, or public figures that relate to health, race or ethnicity, political affiliation, religion, or sexual orientation.”

The removal of those targeting options feels like deja vu now.

During the past couple of years, Meta launched several products that helped clarify the path that we’re on…

1. Advantage Targeting Expansion Tools. Meta launched Advantage Detailed Targeting, Advantage Lookalike, and Advantage Custom Audience. When used, Meta can expand your audience beyond your targeting inputs if more or better results can be found. In some cases, it’s an option that you can turn off. In others, expansion is on by default.

2. Advantage+ Shopping Campaigns. Meta launched its advancements in machine learning and AI to help e-commerce advertisers. When running Advantage+ Shopping Campaigns, no advertising inputs are provided at all beyond a cap on reaching current customers. Instead, Meta relies on signals and historical data.

3. Advantage+ Audience. Meta applied what it was doing with Advantage+ Shopping to create a version for any objective. Advantage+ Audience allows you the option of providing targeting suggestions, with the expectation that delivery can go much broader. If you don’t provide suggestions, the algorithm will focus on pixel data and conversion history as a starting point.

While you can switch back to the old targeting method, Advantage+ Audience is now the default approach.

We could even include Chrome’s phaseout of third-party cookies in 2024 as another critical change that is likely to impact how targeting happens.

Targeting Today

Given all of these trends, the picture of targeting today looks like this…

1. You have fewer detailed targeting options than ever before.

2. Your targeting inputs aren’t always required.

3. When provided, your targeting inputs mean less than ever before because the algorithm can and will go broader.

These are facts and are not debatable. Whether or not you insist on using granular targeting options and you believe they are more effective does not matter. In some cases, the impact of those granular inputs are probably far less than you think because the audience is expanded. In others, you may actually hurt your results by refusing to evolve with the trends.

That isn’t to say that broad targeting works 100% of the time for all advertisers and you should never use granular targeting. Instead, know that the way you are targeting opposes the way Meta wants. That will eventually catch up to you.

What’s to Come

Unless something shocking happens, we’re heading in a rather obvious direction.

1. It’s quite possible that Meta will repurpose Advantage+ Shopping Campaigns for other objectives (this is already in the works for leads). This means the possible removal of all targeting inputs. Before you consider it a bad idea, this also assumes that Meta’s delivery algorithm improves to make it possible.

2. If not #1, Advantage+ Audience becomes the default requirement. No more switching to the old targeting methods. Any targeting inputs you provide, regardless of the objective, will be suggestions only.

3. Detailed targeting options continue to dwindle, eventually settling on a broader category of behavior. Again, this assumes that we’ll be able to use detailed targeting at all soon. But if we do, this approach of broader categories makes the most sense since it gives Meta more control over these smaller interests that end up falling into sensitive areas.

What You Should Do

It’s time to be blunt. There’s no stepping around this. You can’t keep targeting the ways that you always have. And frankly, you may be hurting your results if you are.

The first thing you should do is an audit of your current advertising approach. Maybe it worked five years ago. Does it actually make sense now?

And by “making sense,” I don’t just mean that you’re getting good results. It’s possible you’re still getting decent results in spite of yourself. Are you creating five ad sets per campaign for different cold targeting options? Due to targeting expansion, there’s probably way more overlap in that targeting today than there would have been in the past.

Start embracing some of the targeting methods that will continue to be available in the coming months and years. Experiment with Advantage+ Shopping Campaigns if you’re promoting an e-commerce brand. Start using Advantage+ Audience, both with and without targeting suggestions. Does it matter which one you use? Does that approach impact longevity?

Let me be clear that I did not immediately embrace broad targeting. I resisted the initial Advantage Targeting Expansion options when they were released. Over time, I began to see that they did help results (with some exceptions). I now fully embrace Advantage+ Audience with targeting suggestions.

I’m not necessarily saying to completely abandon something if it works, especially if you’re positive that the alternative does not (though I’d question that). Instead, prepare yourself the best you can for what is likely inevitable. Test broader targeting. Don’t just test it because you hope to prove that it fails. Try to find ways that will make it work for you.

Because one day, and that day is likely not far into the future, you likely won’t have a choice.

Your Turn

Have you embraced broader targeting?

Let me know in the comments below!

The post Meta’s Removal of Detailed Targeting is a Reminder of What’s to Come appeared first on Jon Loomer Digital.

One common point of confusion for Meta advertisers is Meta’s expansion of ad targeting. In some cases, advertisers don’t realize it’s possible at all (but is). In others, it’s completely unclear how much an audience was expanded.

To make things worse, Meta has added new targeting features related to audience expansion that sound similar but are different in subtle ways.

The concept of targeting expansion began with Advantage Detailed Targeting (originally Detailed Targeting Expansion). That same approach was applied to Lookalike Audiences (Advantage Lookalike) and even custom audiences (Advantage Custom Audience).

Those options weren’t good enough. Meta then launched Advantage+ Audience, which essentially combines the three other options to allow advertisers to provide targeting suggestions prior to going broader.

If you’re confused just by reading this intro, it’s understandable. There’s way too much going on in the space of audience expansion. It’s become too complicated, and advertisers are mostly left in the dark regarding when and how expansion happens.

My goal is to shed some light on this. Let’s break down how Meta defines the use of targeting expansion in these cases. I’ll then share my request for how Meta could clear up the confusion with necessary transparency.

By the end, I’ll detail a test that I am starting that could help provide some necessary clarity.

Let’s go…

Advantage Targeting Expansion

As mentioned at the top, there are three types of Advantage targeting expansion. Let’s define each one…

1. Advantage Detailed Targeting. This only applies if you’ve entered audiences within Detailed Targeting (interests and behaviors). If Meta’s systems find improved performance opportunities outside of your targeted audience, the audience can be dynamically expanded to take advantage of those opportunities.

A handful of objectives and performance goals allow you the option of turning this on or off…

But, in most cases, Advantage Detailed Targeting is on by default and can’t be turned off. Here’s an example when the performance goal is to maximize the number of conversions…

2. Advantage Lookalike. This functions similarly to Advantage Detailed Targeting, but it’s specific to the expansion of Lookalike Audiences. When you create a lookalike audience, you select a percentage (from 1-10%) to isolate those people most similar to your source audience.

Let’s assume your lookalike audience is based on the top 1% of those most similar to your source. Advantage Lookalike allows Meta to expand beyond your chosen percentage if better results can be found by doing so.

As is the case with Advantage Detailed Targeting, you are given the option of turning Advantage Lookalike on or off when using certain performance goals.

In other cases, it’s on by default and can’t be turned off.

3. Advantage Custom Audience. This works just like Advantage Detailed Targeting in that Meta can expand beyond your selected custom audience if better results can be found by doing so. The difference here is that you will always have the option of turning this expansion off.

Advantage+ Audience

And finally, Meta rolled out Advantage+ Audience as an improvement to the prior three options. This is Meta’s recommended approach to targeting now. If you use Advantage+ Audience without any customizations, Meta will utilize AI and machine learning to find your audience based on pixel data, conversion history, and prior engagement with your ads.

As you can see in the image above, you have the option of providing an audience suggestion. If selected, you could enter information like detailed targeting, lookalike audiences, or custom audiences. When you do this, Meta will prioritize those suggestions before going more broadly.

If you’re confused by how this is any different than the other three options, Meta explains it here:

Advantage+ audience creates the broadest possible audience to search within, giving Meta’s AI lots of flexibility.

In comparison, Meta’s original audience options, including Advantage options (Advantage detailed targeting, Advantage custom audience and Advantage lookalike), can limit the potential of Meta’s AI which can be less effective.

In other words, the first three Advantage options can expand your audience, but Advantage+ Audience has the ability to expand your audience even more. And that, according to Meta, allows it to get you better results.

Request for Transparency

So, here’s the problem…

When we create an ad set that uses any of these options, we will never know any of the following:

1. Whether the audience was actually expanded
2. How much the audience was expanded
3. The results associated with the expanded audience (outside of your targeting inputs)

We know that the audience can be expanded. We know that it’s likely to be expanded. But, theoretically, it won’t necessarily be expanded at all.

If you take the definitions of these features literally, Meta will only go after people outside of your targeting inputs if it will lead to improved performance. It’s reasonable to assume there are cases when that expansion isn’t required.

Especially if your budget is small or your beginning targeting audience is large. Or maybe you’re getting great results out of the audience you’re using and Meta can’t do better than that.

We simply don’t know. It’s a guess.

There’s a simple (in my non-technical opinion) solution, if Meta wants to fix this. Create a breakdown option for Audience Expansion so that separate rows are created for your Ads Manager results:

1. Targeted (or suggested) audience
2. Expanded audience

This will give us a transparent look at how much our audience was actually expanded — and whether that expansion was truly beneficial.

Of course, that’s not coming any time soon, if ever. It’s a request.

A Test

In the meantime, there are two simple questions I’d like answered:

1. How much are these audiences expanded?
2. How much more is the audience expanded when using Advantage+ Audience?

There won’t be a perfect way to measure this because limitless factors are likely to impact whether the audience expands and how much. But I wanted to run a test that would force Meta to expand the audience and then see if there’s a difference between the approaches.

There are two primary ways you can get Meta to expand an audience when expansion is on:

1. Spend a ton of money
2. Target a tiny audience

I don’t feel like burning money, so I’m going with the second.

I created a campaign with three ad sets targeting a custom audience that should include a few hundred people. The ad sets, as you probably guessed, are different based on the use of expansion.

1. Custom audience only (no expansion)
2. Custom audience plus Advantage Custom Audience
3. Advantage+ Audience plus custom audience as an audience suggestion

I then created an A/B test in Experiments so that there wouldn’t be any overlap in the targeting.

Since our focus is on how much the audience is expanded, I’m going to use Reach as the performance goal. This also allows me to set a frequency cap of 1 impression in 7 days to further force expansion to happen.

Since the performance goal is Reach, we can assume that Meta will gladly expand the audience to simply reach more people. But will it expand more when using Advantage+ Audience than Advantage Custom Audience?

It’s very possible, if not likely, that the amount of expansion is also influenced by the performance goal. Would it matter if I instead optimized for leads? Conversions? Link clicks? Something else?

Let’s focus on one thing at a time. I started this test today, and I’ll report back when I have something of substance to report.

My guess is that the ad set targeting the custom audience without expansion will burn out quickly and may stop delivering entirely. I’ll be curious to see if there’s any difference at all in expansion between the other two.

Depending on these results, I’ll want to run future tests related to different performance goals as well as get a clearer sense of performance between the three approaches.

Your Turn

What’s your experience been with audience expansion?

Let me know in the comments below!

The post How Much Does Meta Expand Your Audience? appeared first on Jon Loomer Digital.

In a previous post, I discussed how you should approach Meta ads targeting now. Things have changed quite a bit, and it’s important that you evolve with those changes. But, what does the future of Meta ads targeting look like?

I don’t have a crystal ball. These are all predictions. But, if you’ve been paying attention during the past few years, you’ll likely agree that these predictions are reasonable, if not likely.

Some of you will read this and feel comfortable, knowing that these changes are unlikely to impact you since you’ve adjusted well to the evolution of Meta advertising so far. But I also know that this will make some of you very uncomfortable.

When is the “future,” exactly? I could see some, if not all, of these changes enacted during the coming year. It wouldn’t shock me if some happened suddenly in the very near future.

I have no inside information. It’s always possible I’m wrong. But, here’s what I expect will happen…

Where We’ve Been Heading

We’ve been trending in a natural direction for a few years now…

1. Thousands of interests removed.

2. Tracking challenges related to iOS 14 and privacy changes impact remarketing.

3. Meta begins expanding targeting beyond the audiences we’ve selected — first as an option and then by default (in most cases).

4. Advantage+ Shopping Campaigns roll out, which eliminate targeting inputs.

5. Advantage+ Audience targeting rolls out, which allows optional targeting “suggestions.” Otherwise, Meta will find your audience based on pixel activity, conversion history, and prior engagement with your ads.

Maybe you’ve resisted it. But there is a very clear, natural progression happening here.

Advantage Audience Expansion Will Be Eliminated

Once Meta started rolling out Advantage+ Audience, predictable confusion resulted. There are now four different features that sound like nearly the same thing.

1. Advantage Detailed Targeting: If Meta’s systems believe that better performance is available beyond the detailed targeting inputs you’ve provided, your audience can be dynamically expanded.

2. Advantage Lookalike: If Meta’s systems believe that better performance is available beyond the lookalike percentage that you’ve selected, your lookalike audience can be dynamically expanded.

3. Advantage Custom Audience: If Meta’s systems believe that better performance is available beyond the custom audiences you’ve provided, your audience can be dynamically expanded.

4. Advantage+ Audience: Advertisers have the option of providing targeting suggestions using detailed targeting, lookalike audiences, and custom audiences. Meta will prioritize matching those suggestions prior to moving more broadly.

The differences are subtle. In each case, you provide initial targeting inputs (though with Advantage+ Audience, they are merely suggestions). Meta can expand beyond that audience to get you better results — though, Advantage+ Audience seems to suggest that expansion definitely will happen.

Advantage+ Audience also has the potential to go much broader. And if you don’t provide targeting suggestions, Meta will use your past conversions, pixel data, and engagement with prior ads to build and evolve your audience.

The typical advertiser will not understand the subtle differences. They also won’t understand that Meta released Advantage+ Audience as the enhancement that is intended to be more effective than the prior three options.

There truly is no reason for Advantage Detailed Targeting, Advantage Lookalike, and Advantage Custom Audience to continue to exist. You can accomplish nearly the same goals (with improved results, according to Meta) by simply using detailed targeting, lookalike audiences, or custom audiences as suggestions — if you use anything at all.

Meta should, and likely will, eliminate those three options. It’s the natural progression, and I’d be surprised if they survived much longer.

Advantage+ Audience Will Become Fixed Default

We’ve seen this progression with other Ads Manager features in the past. Meta makes or plans to make a setting a fixed default. There are protests. Sometimes (like with Advantage Campaign Budget), Meta backs off.

We’ve seen this with Advantage Detailed Targeting and Advantage Lookalike for specific optimizations. You no longer have the option to turn them off.

We’re starting to see signs of this related to Advantage+ Placements. Meta, at the very least, wants to discourage adjusting from the default.

You have limited ability to make any adjustments to Advantage+ Shopping Campaigns, including targeting. The entire purpose of Tailored Campaign setup is that it’s streamlined and you can’t edit defaults.

Meta’s process with these decisions is rather straight forward. They analyze results when advertisers use the default and when they make manual adjustments. If results are consistently superior by keeping the default, Meta will either lock it in or make it difficult to change.

At the moment, advertisers have the ability to bypass Advantage+ Audience and use old targeting methods. But it’s not entirely clear and obvious that this is possible. It’s an intentional design decision to discourage these changes.

Meta will surely monitor to compare results when advertisers use Advantage+ Audience vs. the original targeting options. They have some of these results already, which is why we’re seeing the current design.

It’s logical to conclude that, while there may be isolated exceptions based on objective or optimization, the original targeting options will be discontinued. You will still be able to use detailed targeting, lookalike audiences, and custom audiences as targeting inputs during this phase. But they will only be as suggestions.

I can see this happening first with detailed targeting and lookalike audiences. It’s possible that custom audiences without expansion will survive — or at least for now.

Most or All Manual Targeting Inputs Will Be Removed

Why not keep going?

Once again, this isn’t a particularly bold prediction. We’ve seen it already with Advantage+ Shopping Campaigns. You cannot provide any detailed targeting, lookalike audiences, or custom audiences for targeting — even as suggestions.

Advantage+ Shopping Campaigns, according to reports from Meta, have been more effective than prior Sales campaigns optimizing for purchases. If it can work for Sales, why not for other objectives and optimizations?

There will likely come a time when these targeting inputs won’t be possible for any campaign type. Meta will dynamically determine your targeting based on:

1. The performance goal
2. Past conversions
3. Pixel data
4. Engagement with prior ads
5. Global user engagement data

In a way, detailed targeting will still exist, but only Meta will use it. The data is all there for Meta to find, and your inputs won’t be needed.

I do think this could be problematic given the current Ads Manager structure. Eliminating targeting inputs makes sense for purchases. But Meta may need to provide additional layers of performance goals to provide clarity regarding what you actually want for this to work in other cases.

One could argue that removing targeting inputs could be a smart move for Meta related to privacy and perception, as well. If advertisers are unable to select specific interests and behaviors, the process of delivering ads may seem less “creepy” to non-advertisers.

Maybe Not Now

I can hear the complaints through my computer screen. “This will never work.” There are bound to be reservations about instituting such an approach with Meta’s current advertising feature set. And many of those reservations are valid.

But Meta’s machine learning and AI will only improve. No matter what you think of the effectiveness of Advantage+ Shopping Campaigns, Advantage+ Audience, or any of the audience expansion tools now, think about a year or two from now.

Think about the advancements we’ve seen in AI just this year. A future without targeting inputs shouldn’t seem far-fetched.

Your Turn

Hey, I could be wrong. But I feel strangely confident about these predictions. They don’t feel particularly bold. It’s the natural progression of where we’ve been and where we appear to be heading.

What do you think of these predictions for the future of Meta ads targeting?

Let me know in the comments below!

The post The Future of Meta Ads Targeting 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.

Meta first introduced Advantage+ Audience when it announced AI-powered ad tools in May of 2023. It will sound eerily similar to the other Advantage audience expansion products. There are some important differences.

Let’s take a detailed look at what Advantage+ Audience is, how it works, how to set it up, and my expectations for the future of Meta ads targeting.

What Is Advantage+ Audience?

You have access to Advantage+ Audience if you see this in the ad set…

Advantage+ Audience is a targeting setting that allows Meta to use AI to determine the audience that will see your ads. To determine this, Meta’s systems are constantly learning from your pixel data, conversions history, and people who have engaged with your previous ads and content.

You can choose to either trust Meta to find your target audience for you without any input or you can provide some inputs as audience suggestions. Your suggestions can include:

• Custom Audiences
• Lookalike Audiences
• Age Range
• Gender
• Detailed Targeting

Meta will prioritize reaching people who match these suggestions before expanding to people more broadly.

Meta provides some convincing stats regarding the effectiveness of Advantage+ Audience.

While I don’t care a whole lot about a 28% lower Cost Per Click or Landing Page View (that doesn’t mean a lower Cost Per Action), the 13% lower Cost Per Product Catalog Sale and 7% lower Cost Per Website Conversion are worth notice and potentially significant.

Audience Controls

Audience Controls are tight constraints, rather than suggestions, that Meta must respect when choosing your Advantage+ Audience. This includes:

• Locations
• Minimum Age
• Excluded Custom Audiences
• Languages

This works much like the Audience Controls for Advantage+ Shopping. You may only ship to customers in certain countries or states. Your product may not be available to people under a certain age. Or your product may not be relevant to those who already bought it.

These controls are necessary in those cases.

When You Can’t or Shouldn’t Use It

Advantage+ Audience is not available for the following situations:

• When promoting a Special Ad Category
• Advantage+ Shopping Campaigns
• Advantage+ App Campaigns
• Retargeting campaigns using Advantage+ Catalog

Meta already utilizes AI to generate your audiences for Advantage+ Shopping and Advantage+ App Campaigns.

Meta also recommends that you don’t use Advantage+ Audience generally when remarketing.

Set Up Audience Controls

When you click to Show More Options within Audience Controls, you’ll see minimum age, excluded custom audiences, and languages.

These are the tight constraints that Meta must follow when finding your audience. So, even when finding people beyond your suggestions, these rules will apply.

Here are a few things to consider…

1. Location. First, you will need to select countries or states if you can only ship to certain locations. But you should also consider including only certain countries here, too, depending on your optimization. Unless you optimize for a purchase, you can expect your ads to be delivered primarily to the cheapest countries. By default, Meta will include your home country here.

2. Minimum Age. There’s really no reason to include anything here unless there’s a legal reason to set a minimum age. Ignore the age of your “typical” customer. Meta will sort this out.

3. Excluded Custom Audience. Use this only when necessary. For example, you’re promoting a product that can only be purchased once.

4. Languages. Meta recommends leaving this blank unless you want to show your ads to people in a language that isn’t common to a location.

Set Up Advantage+ Audience

First, a couple of things to keep in mind here…

1. You can provide an audience suggestion, but it’s optional. At some point, you should experiment with both approaches: Providing a suggestion and not.

2. You can switch back to original audience options. If you’re not ready for this, know that it’s not forced on you (yet, at least). You can still go back to the old ways of targeting.

But you can provide custom audiences, lookalike audiences, an age range, gender, and detailed targeting as suggestions.

Just keep in mind that these are not tight constraints. Meta will prioritize these suggestions initially, but your ads can still reach people who wouldn’t qualify. If you have a tight constraint on age, you need to provide it in Audience Controls.

How Is This Different?

If you’re confused by how this is different than simply using Advantage Custom Audience, Advantage Lookalike, and Advantage Detailed Targeting, I totally understand. This stuff is eerily similar.

In both cases, Meta prioritizes the initial audience — at least, at first. In both cases, Meta can expand the audience to reach people beyond that group.

Here are the main differences, the way I understand it…

1. Age and Gender. When you use Advantage Detailed Targeting, Advantage Lookalike, or Advantage Custom Audience, Meta uses age and gender as tight constraints. The expanded audience will respect those settings. That isn’t necessarily the case with Advantage+ Audience.

While you can set a minimum age when setting up Advantage+ Audience using Audience Controls, the age range that you provide is a mere suggestion. The same goes for gender. You may think only women care about your product, but Meta can reach men if it’s determined it will help you get better results.

This may sound crazy, but it’s a matter of trusting the AI. Meta is learning from your data and results. You shouldn’t expect your ads to suddenly get shown to men if only women purchase.

2. Extent of Expansion. Meta actually calls this out specifically when talking about the benefits of Advantage+ Audience.

Advantage+ Audience provides the “broadest possible audience to search within.” Meta even says that this limitation prevents those other options from being more effective. That inability to go as broad limits the AI.

This also goes back to one of my original issues with Advantage Detailed Targeting, Advantage Lookalike, and Advantage Custom Audience. We’ve never known how much Meta actually expands our audience when these are turned on. There’s not a way to see results broken down by people you targeted versus those who were part of the expanded audience.

The result was that most advertisers assumed that Meta was significantly expanding our audiences. But that may not have been the case.

Versus Going Broad

Going broad with targeting (removing all interests, behaviors, custom audiences, and other targeting) has increased in popularity among advertisers. How is this different?

You could set up an ad set using broad targeting without any inputs. You could also use Advantage+ Audience without any targeting suggestions. My understanding is that your ads will be delivered differently in each case.

Or at least slightly differently. We’ve heard about the power of broad targeting, but Advantage+ Audience is another level of AI targeting power. It’s similar to how the targeting power for purchases is greater for Advantage+ Shopping Campaigns than simply going broad when optimizing for purchases.

At least, this is how Meta advertises it. Feel free to test!

When To Use It

Like any strategy, you should experiment and find when it works best for you. If you had asked me a year ago what I thought about broad targeting or any of the audience expansion products, I’d give you a much different answer than I would now. Don’t assume that this is a bad idea.

In my opinion, this is best when optimizing for any type of conversion, especially a purchase (when not running Advantage+ Shopping Campaigns). I’d be wary of using it for top-of-the-funnel campaigns that optimize for link clicks, landing page views, video views, or any type of engagement, but we should still experiment.

The reason I’d be hesitant to use this for surface level engagement is that the algorithm will just work harder to get you those cheap actions. And those cheap actions are often not high-quality actions. And the algorithm won’t care.

That brings up a whole different philosophical discussion and a potential solution if Meta ever wants one. They could provide optimization options for high-quality traffic and engagement to prevent this potential issue.

The Future of Targeting

This is the direction Meta ads targeting has been going ever since the launch of Detailed Targeting Expansion (before it became Advantage Detailed Targeting). More automation. Less control. More AI-powered learning. And ultimately, less transparency in reporting and more trust in the algorithm.

This is just a hunch, but I assume that Advantage+ Audience will eventually completely replace Advantage Detailed Targeting, Advantage Lookalike, and Advantage Custom Audience. There’s simply no value in having them anymore. They are too similar, and keeping them will only confuse advertisers.

We’re getting much closer to a time when we won’t provide any targeting at all. While that may sound scary, the truth is that Meta already has our targeting in the form of historical data. We don’t necessarily need to provide anything because the algorithm already knows who has converted on our website and is engaging with our ads and content.

Watch Video

I recorded a video about this, too…

Your Turn

Have you experimented with Advantage+ Audience? What do you think?

Let me know in the comments below!

The post How Advantage+ Audience Works appeared first on Jon Loomer Digital.

Facebook ads of yore were a collection of advertising obstacle courses and brain-bending puzzles. Meta wants today’s advertising to be as simple as the press of a button. Case in point: The ability to automatically apply delivery recommendations.

You’re likely seeing a constant stream of delivery recommendations these days. You can take it a step further and accept them all.

But, should you?

The Button

Within your Account Overview, you may have seen this…

It reads:

Recommendations are generated when there’s an opportunity that could improve your campaign performance. You can control the types of adjustments that are automated and turn them off at any time.

This sounds scary. Before we do this, we need to learn more about what types of changes fall within these recommendations.

Automatic Adjustments

If you turn that slider on, you’ll see that you do have some control over what delivery recommendations are considered and which you will automatically apply.

Let’s break these down…

Campaign Structure: “Ad sets may be combined so they deliver more efficiently. Ads that are underperforming could be turned off, which may redistribute your budget.”

This seems most relevant to Auction Overlap and Audience Fragmentation. My assumption is that the ads that are turned off are only in relationship to the ad set that was combined.

Audience: “Adjust targeting settings when there’s an opportunity to reach more people who might be interested in your ads.”

This seems to suggest that even if you don’t turn on one of the Advantage+ audience expansion products, Meta may turn it on anyway if it’s believed to help you get more results.

Creative and Format: “Your ad creative may be enhanced when it’s likely to improve performance. This applies to media, text, ad format and other visual elements.”

You have the option of turning on Advantage+ Creative when you put your ad together. If you don’t, it may automatically get turned on (or an element of it may get turned on) if it may help you get better results.

Delivery and Engagement: “Optimize how your ads are delivered and which placements they’re shown in. This includes settings related to how people may engage with your ad, like which outcomes are prioritized.”

This seems a bit vague, but it sounds like it could change how your ad set is optimize (“which outcomes are prioritized”). It also seems to be related to turning on Advantage+ Placements, even if you had manually selected individual placements.

Spend and Schedule: “Your budget will never be changed. Other bid and schedule settings may be adjusted to help spend your budget more efficiently.”

This, again, lacks details. I assume if you used a Cost Cap or Bid Cap, the cap you set may be automatically adjusted if this is on. The only “schedule setting” I can imagine might get adjusted is if you use dayparting — maybe a day or time you had turned off would get turned back on if it would lead to better results.

What Should You Do?

Look, I just came around to broad targeting and (usually) rolling with Advantage+ Placements. I might be a little conservative on this.

But, I am not ready to hand over the wheel completely to Meta.

In order to turn these settings on, you’d need to be comfortable with Meta’s automated assessment globally — in all cases. The problem is that there are often exceptions to when I want to use these things.

Let’s address these one at a time…

Campaign Structure: There might not be a single time I’ve accepted Meta’s recommendation to merge campaigns or ad sets. Usually, it makes no sense to do so. Otherwise, I’ll give up on a campaign or ad set when I decide I’m ready.

I’m keeping this off.

Audience: We often have no choice whether Detailed Targeting or Lookalike Audiences are expanded these days, at least if you are optimizing for some sort of conversion. But if it’s off, it’s because I want it off. And there are times when I’m targeting a custom audience and I absolutely do not want to expand that audience.

I’m keeping this off.

Creative and Format: I’m actually beginning to experiment with Advantage+ Creative a bit more. I’m open to using it. I’m not convinced it’s particularly helpful yet. But I’m moving in that direction. Still, if I have it off it’s because I want it off (for now, at least).

I’m keeping this off.

Delivery and Engagement: First, I can’t imagine being open to Meta automatically changing my optimization goal. I understand how optimization works. I chose my optimization goal for a reason. Don’t change it.

If I’m optimizing for any type of conversion, I’m using Advantage+ Placements. But there are times when I won’t, and that’s largely because of flaws in Meta’s ads optimization. Once again, if I’m not using all placements, there’s a reason for it and I don’t trust Meta with this.

I’m keeping this off.

Spend and Schedule: The problem is that I’m not even sure what this is about. If it’s related to bidding, I don’t do a lot of manual bidding anyway. If it’s about dayparting, I don’t do that either. So… I just don’t have a reason to turn this on.

I’m keeping this off.

It’s not that I’m opposed to adjustments with any of these recommendations. The problem is that I don’t fully trust Meta to apply them globally whenever the algorithm thinks it should. There are too many weaknesses in the system right now.

The ads algorithm is getting better. It’s super smart. But it’s not perfect either. And because of that, I just can’t turn this on yet.

Watch Video

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

Your Turn

Do you automatically apply delivery recommendations, partially or completely?

Let me know in the comments below!

The post Should You Automatically Apply Delivery Recommendations? appeared first on Jon Loomer Digital.

Meta started rolling out Advantage targeting in 2021, allowing the ads algorithm to expand your chosen targeted audience in certain situations. How and when expansion works is still often misunderstood.

It makes sense why. This topic has been a moving target.

In just two years, of course, three different Advantage targeting products with expansion capabilities have rolled out (and a confusing fourth on the horizon). It doesn’t help that the names and rules for how they’re used have evolved during that time.

Let’s clear up the confusion now…

Advantage Detailed Targeting

Originally announced as Detailed Targeting Expansion, Advantage Detailed Targeting was the first audience expansion product available.

When Advantage Detailed Targeting is turned on, Meta will “dynamically expand the audience to reflect where we’re seeing better performance and we may expand your audience further to include similar opportunities.”

This expansion applies only to the Detailed Targeting (interests and behaviors) that you enter, and expansion will not impact restrictions you apply related to location, age, gender, or exclusions.

In the example above, there is a checkbox that allows the advertiser the option of turning it on and off. But it is automatically on (and can’t be turned off) when optimizing for any type of conversion, value, app event, or app install.

In these cases, it will look like this (no checkbox)…

Advantage Lookalike

Advantage Lookalike (originally Lookalike Expansion) came next.

While the audience expansion concept is the same as Advantage Detailed Targeting, the execution is slightly different. Using the Custom Audience that you based your lookalike audience on as a guide, Meta’s system will expand beyond the percentage you selected for your lookalike audience if it’s determined you can get better results by doing so.

Advantage Lookalike is automatically turned on for all conversion, value, and app promotion optimizations. In these cases, it looks like this…

As with Advantage Detailed Targeting, the restrictions (location, age, and gender) and exclusions you set will still apply. Advantage Lookalike isn’t available for Special Ad Categories like housing, credit, employment, politics, and social issues.

Advantage Custom Audience

Next came Advantage Custom Audience.

Once again, Advantage Custom Audience allows Meta to dynamically expand your audience and move beyond your selected custom audience if it’s believed that doing so can improve performance.

This feature will be turned on automatically regardless of optimization when a custom audience is selected. However, unlike the other two options, the checkbox remains and this option can be turned off.

This is probably good as advertisers may want to limit their targeting to a specific custom audience in some cases. But, be aware that this may be turned on — I’ve been burned by this in the past when I thought I was reaching a hyper-targeted group.

Advantage Audience

If you weren’t confused yet, it’s going to start getting confusing now…

If you select both a custom audience and lookalike audience while optimizing for a conversion or other action that won’t allow you to turn off Advantage Lookalike, it will look like this…

But if you optimize for an action like a link click or landing page view (among others) where you have the ability to turn both Advantage Custom Audience and Advantage Lookalike on or off, the name changes to Advantage Audience.

There’s no new functionality here. You just can’t individually turn Advantage Custom Audience and Advantage Lookalike on or off. It’s a group selection.

Advantage+ Audience

And now it’s going to get ridiculous.

Yes, it looks like I just listed Advantage Audience twice. But, this time I’m actually listing Advantage+ Audience (emphasis on the “+”). In a May 11, 2023 announcement about new AI-powered ads tools, Meta provided details about Advantage+ Audience.

Advantage+ Audience is an AI-powered targeting tool that will develop an audience for you based on pixel activity, conversion history, and ad engagement. You have the option of providing targeting suggestions that Meta will initially prioritize. You can also use Audience Controls as tight constraints.

This all sounds very similar to Advantage Detailed Targeting, Advantage Lookalike, and Advantage Custom Audience, but there are slight differences.

1. Advantage+ Audience uses AI to generate your audience. This is why it includes the “+” in the name and the others do not.

2. Advantage+ Audience has the ability to go broader than the others. Meta tells us this, but it would have been difficult otherwise to know for sure since there is a lack of transparency in reporting.

3. Advantage+ Audience uses age and gender as suggestions. When turning on Advantage Detailed Targeting, Advantage Lookalike, and Advantage Custom Audience, age and gender settings are used as tight constraints.

My guess is that Advantage+ Audience will eventually replace the other three.

Should You Use Advantage Targeting?

Okay, back on topic. Let’s focus on the three actual features relevant to this post:

• Advantage Detailed Targeting
• Advantage Lookalike
• Advantage Custom Audience
• Advantage+ Audience

I was initially pretty terrified of these features. I put in certain targeting and I want to use that targeting! But with time, it’s grown on me. Expansion is that middle ground between hard constraint targeting and going broad.

The way these features are defined, targeting expansion can’t hurt you. It can only help you. The audience may not be expanded it all. But if it is, it’s because that expansion can get you better results.

The problem? We have no idea whether your audience was actually expanded, how much it was expanded, or how performance was impacted by that expansion.

There should be a pretty simple solution to this. Meta should add a breakdown for audience expansion that adds rows to your report for your intended audience and the expanded audience. Without that, we’re left guessing regarding whether this is actually beneficial.

More transparency could also give advertisers more confidence in these products.

Your Turn

What’s your experience been with Advantage targeting expansion products?

Let me know in the comments below!

The post Advantage Targeting: How Meta Audience Expansion Products Work appeared first on Jon Loomer Digital.

Facebook is rolling out Advantage Custom Audiences to advertisers, which will potentially expand your targeting when a custom audience is selected.

Wait… This isn’t new, right? Oh, it is?

You’d be forgiven if this sounds like something that’s already been around for a while. A couple of similar audience expansion features have been rolled out to the Advantage product line during the past year. But this, indeed, is new.

Let’s break down what this is, how it’s applied, when you’d use it, and when you absolutely should avoid it.

What Is This?

First, let me be clear that this is a rollout. I don’t have it in most of my accounts.

But, if you enter a custom audience into targeting and you see a checkbox for Advantage Custom Audience like the image below, congrats. You have it.

When Advantage Custom Audience is turned on, your custom audience will be targeted, but targeting can be expanded to people outside of that custom audience if it can improve performance.

Sound familiar? Yeah, that’s a lot like Advantage Detailed Targeting (formerly Detailed Targeting Expansion)…

and Advantage Lookalikes (formerly Lookalike Expansion).

In both cases, the audience can be expanded beyond what you enter if it can improve performance. But, of course, those features were unique to Detailed Targeting and Lookalike Audiences.

When Is It On?

How and when Advantage Custom Audiences are turned on are a bit different than for Advantage Detailed Targeting and Advantage Lookalikes. You can turn Advantage Custom Audiences on, no matter the objective. The other two are objective-specific.

Another difference is that even if Advantage Custom Audience is turned on by default (it will be), you can turn it off. Originally, this was the case with Advantage Detailed Targeting and Advantage Lookalikes. But now, you are unable to turn those two options off (at least in most cases).

Once you enter a custom audience, you can turn this on (assuming you have the feature), regardless of the objective.

When Should You Use It?

Admittedly, I’ve been a bit skeptical of the other two audience expansion products. I’ll get to that more in a moment. But, there is actually a good reason to use Advantage Custom Audiences.

Far too many advertisers struggle with understanding how to set budgets when targeting custom audiences. In almost all cases (unless you’re a big brand), these audiences are going to be small. It doesn’t matter whether it’s website visitors, page engagement, or your email list. We’re usually talking about a few thousand people — or at least under 100,000.

If you treat these audiences the way you do broad targeting and throw a $100 per day budget on it, you’re going to torch that audience pretty quickly. The frequency and CPM will also jump.

Assuming that your messaging isn’t unique to the audience you’re targeting (more on that in a moment), expanding the audience would make a lot of sense.

It’s important to understand how this works. The audience doesn’t immediately jump from 5,000 to 5,000,000 (even if the “potential” audience may look that way). The audience will only expand if it will improve results. The custom audience will still be the core audience used for targeting.

So, expanding your audience could actually improve your average frequency and CPM. Your audience is used in a similar way to how it’s used to generate a lookalike audience. But in this case, that source audience is still used for targeting.

When You Definitely Shouldn’t Use This

When I first heard that this feature was being tested, I was concerned. Audience expansion makes very little sense to much of our remarketing.

Consider the abandoned cart scenario. In that case, you are targeting people who added a specific product to their cart and didn’t purchase. You may create an ad that says something like, “Hey, did you forget something?” and showcase that product. This ad, of course, would only make sense for those in a specific audience.

The same would apply for cross promotions and up-sells. In either case, the ad copy may refer to something specific that a customer did or bought that’s related to another product. This would make no sense to an expanded audience.

In other words, be extra careful with your remarketing. If the ad copy and creative will only make sense to your targeted audience, make sure to turn off Advantage Custom Audience.

Transparency, blah, blah, blah…

If you’ve listened to my podcasts or are in the PHC community, you’re probably tired of hearing me talk about this by now. But I’m not going to stop until this is fixed.

Audience Expansion is a fine little feature if it’s effective. The problem is that we have very little evidence to prove this. It’s not that it’s not working. We just don’t know because it’s all left behind the curtain.

First, we don’t even know if the audience is expanded when this is turned on. Yes, in theory, it can be expanded when any of these features is turned on. We never know when the audience is expanded, how much it’s expanded, or how many of your results came due to expansion.

And that would be helpful, right? Give me a breakdown showing performance of my targeted audience compared to the expanded audience. This could then sell the feature, underscoring the benefit.

This doesn’t exist. You can split test two ad sets when expansion is on and when it’s off. But that’s the closest we get to fully understanding whether this feature is worthwhile. Beyond that, it’s all a guess.

Watch Video

Your Turn

Do you have Advantage Custom Audiences? What do you think, will you use it?

Let me know in the comments below!

The post Facebook Advantage Custom Audiences: What You Need to Know appeared first on Jon Loomer Digital.