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.

A long-running mystery in the era of algorithmic Meta ad delivery can finally be answered: How much do our targeting inputs matter?

I’ve run a test that reveals how much Meta distributes ad delivery between my remarketing audiences and prospecting while relying on algorithmic targeting and expansion. The results are surprising, encouraging, and enlightening.

This post is a bit of a rabbit hole, but it’s worth it. Let’s get to it…

Background and Historical Context

Years ago, targeting was simple. We made a series of selections using custom audiences, lookalike audiences, detailed targeting, and demographics. We then expected that our ads would reach people within those groups.

But, that all began to change with the introduction of Advantage audience expansion. At first, it was an option. Then expansion became the default for detailed targeting and lookalike audiences with certain objectives. And finally, Meta introduced the next level of hands-off, algorithmic delivery: Advantage+ Shopping Campaigns and Advantage+ Audience.

Luckily, Meta made audience segments available to provide important visibility into how Advantage+ Shopping Campaigns were delivered. We could then see how much of our budget went to our engaged audience, existing customers, and new audience (or prospecting). This was critical since these campaigns didn’t allow for any of the audience inputs we typically expected.

Meanwhile, advertisers confronted with the unknown of how Advantage+ Audiences delivered their ads often chose the greater control found with original audiences. But even then, audiences often expanded. The mystery went unanswered.

And then Meta expanded access to audience segments for all campaigns that utilize the Sales objective (this feature is still rolling out). While this includes Advantage+ Shopping Campaigns, it also applies to any manual campaign that utilizes the Sales objective. And this doesn’t require optimizing for a purchase.

This new option opened up a world of possibilities for testing and transparency. I recently wrote a blog post about the test I was starting. And now I’m ready to share my initial results.

My Test

The basis of this test was simple. I wanted to use audience segments to get a better sense of how my ads were delivered when using the following targeting setups:

1. Advantage+ Audience without suggestions
2. Advantage+ Audience with suggestions using custom audiences that match my audience segments
3. Original Audiences using custom audiences that match my audience segments — with Advantage Custom Audience turned on

This was all part of a single campaign that utilized the Sales objective and a website conversion location.

Since the purchase conversion event isn’t required for this objective, I used this test to promote a lead magnet that utilizes the Complete Registration standard event.

In terms of demographics, I used all ages in the countries of the United States, Canada, United Kingdom, and Australia. These are the four countries that make up the largest percentages of my customer base.

I initially started running the ad sets concurrently before I quickly switched gears and ran one at a time without distraction. I spent a modest $270 (or so, not exact) for each ad set.

I contend a large budget wasn’t necessary for this test since my questions were answered rather quickly. My focus wasn’t on whether any of these ad sets were “successful” in terms of generating conversions. Far too many factors impact Cost Per Conversion (the ad, the offer, the landing page), and that just wasn’t a concern here.

Granted, spending thousands of dollars would give me more confidence in these results. And I’ll certainly be monitoring whether what happened here continues with my advertising in the future. But, there were very clear learnings here, even with a modest budget.

My primary concern was simple:

1. How will ads get delivered?
2. How will my budget get spent?
3. How will it be distributed between my engaged audience, existing customers, and new audience?

We have answers.

Defining My Audience Segments

A critical piece to this test is how I’ve defined my audience segments. This is done within your ad account settings.

1. Engaged Audience. These are people who have engaged with my business but have not made a purchase. I’ve used a website custom audience for all visitors during the past 180 days and a data file of all of my newsletter subscribers.

2. Existing Customers. These are people who have made a purchase. I used website custom audiences and data file custom audiences for those who have bought from me before.

There will be overlap between these two groups, of course. A Meta representative confirmed that if anyone is in both groups, they will only be counted as an existing customer.

Once these are defined, we’ll be able to use breakdowns by audience segments in Ads Manager to see results of sales campaigns for each group.

Test Group 1: Advantage+ Audience Without Suggestions

This may have been the biggest mystery of all. When you use Advantage+ Audience without suggestions, who will see your ads?

Meta gave us some clues in their documentation, indicating that remarketing was likely a big part of where delivery starts.

But this passage isn’t definitive, and I wanted to prove this actually happens — or doesn’t. Well, it happens. Boy, does it happen.

I didn’t provide any audience suggestions, yet a very large chunk of my budget was spent on remarketing to my defined audience segments. More specifically, percentages dedicated to my engaged audience and existing customers…

1. 35.4% of amount spent
2. 23.7% of impressions

That’s incredible. I never would have expected the percentages to be that high. Note that the percentage of impressions is lower because the CPM to reach my audience segments is nearly twice as high as that for the new audience.

This is a relief. While I’ve trusted in Advantage+ Audience up until now, I generally provide audience suggestions because of that small amount of doubt in the back of my mind. But, this proves that Advantage+ Audience doesn’t require suggestions to reach a highly relevant audience.

Test Group 2: Advantage+ Audience With Suggestions

This got me thinking. If Advantage+ Audience without suggestions results in spending 35.4% of my budget on remarketing to my audience segments, what would happen if I provided suggestions? More accurately, what if I provided suggestions that were custom audiences that exactly match the definitions of my audience segments?

It’s reasonable to assume that even more of my budget would be dedicated to these groups. Once again, if we were to take Meta’s explanation of how Advantage+ Audience works, that’s a reasonable explanation. Meta says that if you provide an audience suggestion, they will “prioritize audiences matching your suggestions, before searching more broadly.”

Well, here’s what happened…

So that you don’t have to do any math, here are the percentages dedicated to my engaged audience and existing customers when using audience suggestions that matched those audience segments…

1. 32.4% of amount spent
2. 29.0% of impressions

By comparison, here are the percentages when not providing any suggestions:

1. 35.4% of amount spent
2. 23.7% of impressions

So, a higher percentage (by 3%, but still higher) of my budget was spent on reaching my audience segments when not providing suggestions than when using custom audiences that matched those audience segments as suggestions. While the percentage of impressions dedicated to those groups was higher, that’s because the CPM to reach my new audience was higher with this approach.

If we hadn’t first tested Advantage+ Audience without suggestions, we’d say that this test proved that Meta did in fact prioritize reaching the audience suggestions before going broader. But, since at best there was no difference in prioritization when not providing any suggestions at all, it’s inconclusive.

My take: Audience suggestions are optional, and in some cases they are unnecessary. If you have an established ad account with extensive conversion and pixel history like I do, you probably don’t need it. In fact, it may even be (slightly) detrimental.

Test Group 3: Original Audiences Using Advantage Custom Audience

Many advertisers have chosen to use original audiences instead of Advantage+ Audience because they don’t trust the lack of transparency of algorithmic targeting. So, I wanted to test one more thing that could be proven with audience segments.

Audience segments won’t help us with better understanding ad distribution with Advantage Detailed Targeting or Advantage Lookalike. While they will help us understand how many of the people reached were already connected to us, it won’t answer questions about how much the audience is expanded — and how that compares to using Advantage+ Audience with or without suggestions.

But, we can learn a lot from how expansion works with Advantage Custom Audience. In that case, Meta should prioritize the custom audiences we provide before expanding and going broader. Technically, it may not have to go broader, and we don’t know how much broader it goes when it does.

So, I ran a test that was similar to the one where I used Advantage+ Audience with suggestions. In this case, I used original audiences and provided the custom audiences that match my audience segments. And then I turned Advantage Custom Audience on.

Here are the results…

Here’s how that breaks down by budget spent and impressions towards the original custom audiences…

1. 26.4% of amount spent
2. 24.1% of impressions

Interesting! In this case, we’d assume that the audience would expand the least and a higher percentage of the budget would be spent on the custom audiences. But, this approach actually resulted in the lowest percentage of budget spent on those groups. The percentage of impressions dedicated to those groups is about the same as when using Advantage+ Audience without suggestions.

Another point to note is that the overall CPM was highest with this approach, though it’s not much higher than when using suggestions. That’s largely driven by a higher CPM to reach the new audience.

The Results: Overall Evaluation

To recap, here are each of those ad sets in one view…

There’s no reason to split hairs here about which approach led to spending more or reaching more of my audience segments. It’s within a margin of error related to randomness that could flip if we tested again — or continued the test.

The main takeaway is this: The overall breakdown in distribution between my remarketing audience segments and new/prospecting audiences was virtually the same for each approach. It made very little difference when using Advantage+ Audience without suggestions, Advantage+ Audience with suggestions, or original audiences using custom audiences and Advantage Custom Audience turned on.

This provides strong evidence that Advantage+ Audience does exactly what Meta says it does. At least in my case, there’s strong evidence that using suggestions is completely unnecessary — or marginally impactful.

I’m also a bit surprised that using the original audiences approach resulted in as much expansion as it did. I expected delivery to hold closer to the custom audiences that I provided — at least in comparison to using Advantage+ Audience.

I didn’t want Cost Per Conversion results to be a distraction in this test because they were not a priority when evaluating distribution. But in case you’re wondering, those results followed very similar trends. Each ad set generated virtually the same number of conversions (within a range of randomness). But, Advantage+ Audience without suggestions provided the most conversions, followed very closely by the other two approaches.

Contributing Factors

It’s important to remember that while these results are generally reflective of how algorithmic ad delivery distributes our ads, they are also unique to me and how this test was set up. There are several factors that may have contributed to what I saw, and you may get very different results.

1. Budget. As I’ve said before, a lower budget still gives us meaningful information here. But, it’s reasonable to expect that the more money I spend, the less will be spent on my audience segments, audience suggestions, or custom audiences. Those audiences will become exhausted and more would likely be spent on the new audience.

2. Audience segment sizes. Very closely related to budget, but this clearly impacts the volume of results I can see from remarketing to these groups. The total sizes of these groups for my test are roughly over 200,000, but closer to 100,000 when limited by the four countries I targeted. The smaller this pool, the less can be spent there.

3. Time elapsed. It’s reasonable to assume that the greatest distribution to these audience segments and custom audiences will happen in the beginning, prior to growing expansion to new audiences. This is again related to the sizes of the audiences and the rate of exhausting them. None of these ad sets ran for a full week, so those percentages would likely drop with time.

4. Conversion event. Since I’m still in the very early stages of analyzing results using audience segments, it’s not clear how much the conversion event used for optimization impacts distribution. We know it does — Meta will make algorithmic changes to find people willing to perform the action that you want. But, it’s not clear how much the event impacts distribution to audience segments, if at all. I used Complete Registration for the conversion event here. Distribution may be different for purchases or custom events.

5. Ad account history. There’s a strong argument that can be made that I should use Advantage+ Audience and there’s no reason to provide audience suggestions. But, that doesn’t mean that’s the case for everyone. It’s possible this is viable for me because of an extensive ad account history with pixel and conversion data to pull from. New accounts, new pixels, or websites that get minimal activity may not have the same advantage. They may see much different results here.

6. Campaign construction. I went back and forth on how to run this. I didn’t run this as an A/B test because I wanted to evaluate natural distribution, rather than forcing delivery without overlap. I also chose to run these ad sets at separate times, rather than concurrently. Even though they ran separately, overlapping delivery was likely (some people may have seen the same ad from multiple ad sets). These decisions likely impacted my results.

Overall, this has been a fun test, but it’s also incomplete. These are numbers I will continue to monitor with my ads going forward to see how it plays out in the future.

Your Turn

Have you run a similar test of manual sales campaigns to see how ads are distributed for you? What did you learn?

Let me know in the comments below!

The post How Meta’s Algorithmic Audience Targeting Impacts Ad Distribution: A Test appeared first on Jon Loomer Digital.

Now that audience segments are available for manual Sales campaigns, it opens up all kinds of fun opportunities for testing and learning. That’s what this post is all about.

If you’re not familiar with audience segments, they’re set within your Ad Account Settings. You can define your Engaged Audience and Existing Customers.

This information can then be used to provide greater insight into your reporting. Using breakdowns, you can generate separate rows for each of these groups — as well as “New Audience” (those who qualify for neither group).

This transparency was helpful, even necessary, for Advantage+ Shopping Campaigns, which are driven almost entirely by algorithmic targeting without the advertiser’s input. These audience segments help answer questions about who is seeing our ads.

Now that audience segments are available for manual Sales campaigns, we can use this to answer some similar questions that have gone unanswered — until now.

Here are three ways you can leverage audience segments to get greater insights into your manual Sales campaign reporting. At the end, I’ll also provide some surprising results of what I’m seeing…

1. Advantage+ Audience without Suggestions

When you create an ad set that uses Advantage+ Audience, you have the option of providing an audience suggestion.

If you don’t, ad delivery will be entirely algorithmic. Meta says that their “AI uses lots of information to find your audience” — like past conversions, pixel data, and prior engagement with your ads.

Here’s a screenshot of that explanation…

That sounds a whole lot like remarketing, right? In other words, even if you don’t provide an audience suggestion, Meta’s AI should — in theory — prioritize showing ads to people you’d otherwise select to target.

I’ve long wondered whether using an audience suggestion mattered. I’ve decided that while it may not make a difference, it can’t hurt.

But, what actually happens? Does Meta’s AI prioritize remarketing audiences like their documentation claims?

Thanks to audience segments, we can test this. Define your audience segments as thoroughly as possible.

This is how I defined my Engaged Audience…

And my Existing Customers…

Next, create a Sales campaign with Advantage+ Audience without providing an audience suggestion. You will then be able to use Breakdowns by Audience Segment to see how many of the people you reached fall within Engaged Audience, Existing Customers, or New Audience.

2. Advantage+ Audience with Suggestions

We can also use audience segments to help answer our questions about whether providing audience suggestions makes a difference.

As I said in the prior section, I tend to use audience suggestions. It’s partly out of habit. But it’s also out of a belief that, at best, it can help the algorithm get started. At worst, it shouldn’t hurt.

Back to Meta’s documentation. If you provide an audience suggestion, Meta says that they will “prioritize audiences matching your suggestions, before searching more broadly.”

Again, let’s screenshot this for emphasis…

In theory, if we were to provide suggestions matching our Engaged Audience and Existing Customers, we should see Meta’s explanation above reflected in our breakdown by audience segments.

So, let’s do that! Create a Sales campaign using Advantage+ Audience. Provide audience suggestions that match your definitions of Engaged Audience and Existing Customers exactly.

The reason for this approach is simple. There’s no reason to provide detailed targeting or lookalike audiences as suggestions since we can’t use those to define our audience segments. Because of that, we’ll never know for sure whether people in those audiences saw our ads.

Since we’re told that Meta AI will prioritize our audience suggestions before going broader, we can prove that one way or another by using the exact custom audiences for suggestions that we used to define our audience segments. When we breakdown our results, we should see that reflected.

In theory, of course.

3. Original Audiences with Advantage Custom Audience

I’ve mostly abandoned original audiences (and Advantage expansion tools that go with them) since the rollout of Advantage+ Audience.

Original audiences feel like old strategies, and we should use Meta’s new and improved tools. Advantage+ Audience works in much the same way that Advantage Detailed Targeting, Advantage Lookalike, and Advantage Custom Audience, but Meta says that Advantage+ Audience is better and more advanced.

Back to Meta’s own documentation on Advantage+ Audience, this is spelled out:

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

Based on Meta’s own words, we assume that these work similarly, but Advantage+ Audience has the ability to go much broader (and lead to better results). So, the assumption is that if you turn on audience expansion with original audiences, the audience will expand — but your original inputs may be more respected.

Once again, we need to stick with the topic of custom audiences since these are what can be verified with audience segments. If we provide all of the same custom audiences that were used in our audience segments and turn on Advantage Custom Audience, what would happen?

How many of the people reached would be from our custom audiences? How many would be from expansion? And how does this compare to when using Advantage+ Audience?

We can test this! Once this is set up, use the breakdown by audience segment to see how your ads are distributed.

Initial Learning

I actually started part of this test already. The early results represent a small sample size, and in some cases they have been surprising.

It’s not clear how much the conversion event matters. Will your Engaged Audience and Existing Customers be used differently depending on whether you optimize for a purchase, lead, or something else?

Other factors like the sizes of the audience segments, sizes of the custom audiences used for suggestions, budget, and time may all contribute.

My initial test used a custom event for 60 second website views as the conversion event. The results were staggering. When providing audience suggestions, less than 1% of my budget was spent on them. When providing no suggestions, it was only slightly better.

But, I started a new test and the results have (thankfully) adjusted. Distribution to my Engaged Audience and Existing Customers has increased significantly, regardless of which approach I’m taking. These results have increased my faith in Meta’s claims that remarketing happens, regardless of whether you provide audience suggestions.

I’ll hold off on sharing specifics until I’m done. Until then, I encourage you to test this, too.

A Note on “Sales” Campaigns

Something that flies a bit below the radar is that you don’t technically need to optimize for purchases when running a Sales campaign. Because of that, you could run tests like I describe in this post while optimizing for any website conversion event (leads, registrations, custom events, and whatever else you use).

Sales is simply how you defined your campaign objective.

It doesn’t determine how your ads are optimized. This is defined by your performance goal and conversion event.

This is the case with Advantage+ Shopping Campaigns, too. Yes, it’s super confusing. You don’t need to optimize for SALES when running Advantage+ Shopping or manual Sales campaigns.

Your Turn

Have you run a test like this? What have you seen?

Let me know in the comments below!

The post Leverage Audience Segments for Manual Sales Campaigns appeared first on Jon Loomer Digital.

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.

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.

Which group of people should you target with your Meta ads? Targeting could be the difference between your ads succeeding and failing.

Of course, you can overthink this, too. You can spend a lot of time trying to find the perfect audience when, in reality, it may have been best to go as broad as possible.

You have a whole bunch of options available to you. Consider this your home base for all things targeting. Let’s walk through every possible lever you can pull to impact the people you reach with your ads…

Advantage+ Audience

Meta first introduced Advantage+ Audience in late 2023 as an advancement in machine learning and algorithmic targeting. This is default method of targeting for all manual campaigns.

The beauty of Advantage+ Audience is that any targeting inputs are purely optional. If you don’t provide an audience suggestion, Meta will prioritize things like conversion data, pixel history, and prior engagement with your ads.

Otherwise, Meta will prioritize your audience suggestion prior to going much broader.

Audience Controls are the few targeting constraints that you can provide. Meta will not deliver ads to people outside of designated locations, minimum age, excluded custom audiences, or languages determined here.

Otherwise, any other targeting inputs provided — including custom audiences, lookalike audiences, detailed targeting, gender, and age maximum — are considered suggestions.

Original Audiences

If you’d like to go back to the way we did prior to Advantage+ Audience, you can click the link to switch back to original audiences. But you’ll get a warning that doing so is unlikely to lead to better results.

Custom Audiences (General)

This is the first area you can use to refine your targeting. If you have created a custom or lookalike audience, you can enter it here. We’ll discuss in a moment what these are.

You can also choose to exclude a custom or lookalike audience from targeting. This is especially useful if you are promoting a product that cannot be purchased twice.

Custom Audience Types

Custom Audiences are groups of people who are connected to you in some way — they’ve engaged with you, bought from you, are on you email list, or visited something you own.

You can create a custom audience from the Audience section. Here are examples…

1. Website Custom Audience

Website Custom Audiences allow you to segment your website visitors for targeting. You can build these audiences because you utilize the Meta pixel or conversions API on your website. Here are some examples.

All website visitors…

People who visited specific web pages…

Visitors by time spent…

And from your events (like a purchase)…

2. Customer List Audience

You can upload your customer list of names, email addresses, phone numbers, and physical addresses and have Meta match up those people with users for targeting.

3. App Activity Audience

Create an audience of people based on their engagement with your app…

4. Catalog Audience

Segment people based on their engagement with your product catalog…

5. Video Engagement Audience

Segment people based on the depth of engagement and specific Facebook video watched…

6. Instagram Account Audience

Isolate those people who have engaged with your Instagram account, assuming it’s been connected to your Business Manager.

7. Lead Form Audience

Isolate those who have opened, opened but didn’t submit, or opened and submitted your lead form.

8. Events Custom Audience

Create an audience of people who engaged with your Facebook event…

9. Instant Experience Audience

Focus on those who opened or clicked on a link within your Instant Experience…

10. Facebook Page Engagement Custom Audience

Isolate those who engaged with your Facebook page in some way…

11. Shopping Custom Audience

Segment those who engaged with your Facebook or Instagram Shop…

12. On-Facebook Listings Custom Audience

Create an audience of people who interacted with the on-Facebook listings from your Marketplace catalog…

13. AR Experience Custom Audience

Create an audience of people who opened your AR experience on Facebook or Instagram…

Lookalike Audiences

When you create a Lookalike Audience, Meta will look for people who are similar to those who are already connected to you in some way.

The source audience will be a custom audience. The Lookalike Audience will be created by country and using anywhere from the top 1 to 10% of those in that country who are similar to this group.

Lookalike Audiences are often used when your custom audience is small and ineffective because there aren’t enough people to target.

Advantage Lookalike

Advantage Lookalike is also one of the Advantage audience expansion products that is only available with original audiences.

When turned on, Meta will expand your audience beyond the selected lookalike percentage if it will lead to better results. In some cases, Advantage Lookalike is on and cannot be turned off.

Location

You can select a location or multiple locations to filter your targeting. Only people living in or recently in that location, while also satisfying the other targeting requirements, will be considered.

You can include locations by country, state/region, city, postal code, address, DMA, or congressional district.

If you browse, you can select countries and regions manually or choose to go worldwide.

You can also exclude locations.

Age

The default, depending on your location, may be people 18 years and older. In some cases, you may be able to target people down to 13 years old. In others, the minimum age may be higher than 18. This will depend upon the laws and restrictions based on location and promotion.

Gender

By default, you will target all genders. You can choose to limit your targeting to men or women only, though that may be restricted if you are promoting a special ad category.

Detailed Targeting

Detailed targeting allows you to reach people by demographics, interests, and behaviors. Most of this information is provided within user profiles or collected based on activities within the Meta family of apps.

Meta has removed many interests and behaviors from targeting during recent years, largely due to privacy laws and restrictions.

You can also exclude people based on this information.

Advantage Detailed Targeting

Advantage Detailed Targeting is another of the Advantage expansion tools that are only available with original audiences.

When turned on, Meta can expand your audience to reach people beyond the detailed targeting that you selected if it will improve ad performance. Your exclusions, locations, age, and gender will continue to be respected.

As is the case with Advantage Lookalike, there are cases when Advantage Detailed Targeting is automatically on and cannot be turned off.

Languages

This is set to All Languages by default, but you can specify specific languages if you choose. In most cases, Meta recommends that you keep this blank.

Strategies

As I mentioned at the top, many advertisers have opted to go completely broad recently and forgo all other targeting considerations. You should at least experiment with that.

Others go with a mixture of Lookalike Audiences and Detailed Targeting for their cold targeting. While some swear by it, I’ve mostly abandoned this approach when prospecting.

I haven’t completely eliminated warm targeting from my mix, though. I will still use custom audiences for targeting in specific cases, especially for exclusions. In some cases, I’ll use custom audiences and turn Advantage Custom Audience on to give Meta the ability to go broader if necessary.

But again, not everyone believes in this approach. Some will tell you that remarketing is dead and is completely unnecessary. That if you go broad, the algorithm will naturally start with those who would be in your remarketing audience.

Find what works for you!

Your Turn

How do you approach targeting?

Let me know in the comments below!

The post The Ultimate Guide to Meta Ads Targeting 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.