How to Get Ahead of Facebook’s 2024 Audience Targeting Changes

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2024 Targeting Changes: The Truth

One point of clarification here: the new audience feature is called “Advantage+ Audience.” At times I call this Advantage Detailed Targeting (previously called Expanded Targeting), which was the old option Facebook gave you for expanding the audience; that’s because functionally it’s close to identical to this new feature. However, the correct term for this new feature is Advantage+ Audience. It looks likely that Advantage+ Audience will replace the various Advantage Detailed Targeting options going forward.

The main difference between the old Advantage Detailed Targeting (Expanded Targeting) and the new Advantage+ Audience is that with Advantage+ Audience, Facebook can ignore your age and gender parameters if the AI determines something outside your specifications will work better. Whereas the previous options would always operate within these set parameters, even as they expanded the audience.

  • What do these new audience targeting changes mean for authors? Facebook is making Advantage+ Audience mandatory come 2024. This feature is already mandatory on many accounts. This functions essentially the same as the “expanded” audience feature (since renamed Advantage Detailed Targeting), where Facebook takes the targeting information you give it (say, EL James) and then its AI targets people within that audience and people it thinks are similar, but aren’t actually in that audience (essentially a Lookalike audience of the selected interest(s)). The only difference with Advantage+ Audience is that it can override the targeting information you input, from the interests to things like gender / age.
  • How big a problem is this for us as authors? Based on the current data we’ve analyzed using the Advantage+ Audience feature, not a problem at all. At worst, performance is likely equivalent; at best, it might be improved and also make things easier to scale since Facebook will increase the audience size.
  • Separating reality from rumor: the only change here is that Facebook is making Advantage+ Audience mandatory come January 2024.
    • Not happening: Facebook is not eliminating the Traffic objective; that will still be available in January 2024 and there are no suggestions whatsoever that they have any plans to remove it.
    • Not happening: Facebook is not eliminating audience targeting entirely; it still takes the audience(s) you give it to target as a suggestion / starting point, it can just expand beyond those audiences now to target people its AI thinks are similar.
    • Not happening: Facebook is not emphasizing the Reach objective (which optimizes for the most impressions) or pushing advertisers toward using that. You do not need to start using Reach, and it’s not a recommended objective for authors. Facebook has always been designed around the Sales (Conversion) objective, wherein it can use the data it receives from the Pixel (tracking code) to find out who is purchasing from your site, then finding more people who are similar. Use Traffic ads if you’re selling on Amazon and Sales ads if you’re selling direct.
  • How to get ahead of these changes before 2024 rolls around: have a solid process for testing your audiences (watch the step-by-step walkthrough below, pause the video, and follow along as you set up your own ads) and start testing Advantage+ Audiences today. Don’t hold out with the normal audiences, not test anything, and then get dragged kicking and screaming into the mandatory rollout in January 2024. If you test now and have the data, then the transition to the new audience targeting system will likely be seamless.

How to Set up a Facebook Audience Test: Step-by-Step Walkthrough

This is a step-by-step walkthrough of how to test audiences as well as setting up an ad using current best practices.

Audience Testing Process

Start by testing authors if you don’t have any audiences that work; they tend to perform the best. You can test the authors individually (e.g., A100 = James Patterson, A101 = Lee Child etc.) or test a group of authors aggregated together, as we did here (e.g., A100 = James Patterson, Lee Child, Gillian Flynn, Harlan Coben, Jo Nesbo, Lisa Gardner, Karin Slaughter, Patricia Cornwell, Michael Connelly, and David Baldacci). This audience is effective for thrillers / mysteries / crime.

The Big 6 Romance author audience mentioned that works well as a recommended starting point for contemporary, paranormal, and sci-fi romance is: EL James, Sylvia Day, Diana Gabaldon, Danielle Steel, Nora Roberts, and Contemporary Romance.

Don’t narrow by a bunch of different interests, age ranges, etc. and overcomplicate things during your initial audience test. Bigger audiences tend to perform better from a CPC perspective and are much more scalable / easy to manage. Facebook also seems to favor larger audiences with Advantage+ Targeting. Once you have some audiences that work, like we had here, you can test variants (narrowed, combined with other interests etc.) of these working audiences to see if that improves performance.

Here’s a list of 5 audiences that are a good starting point for your initial test. All of these have Advantage+ Audience enabled, where applicable:

  1. an aggregate group of popular authors in your genre (e.g., like the author audiences mentioned above)
  2. the genre (e.g., detective fiction, mystery, paranormal romance, romance novels, etc.; if multiple genre interests are relevant, you can test more than one; I’d split the genres out into separate ad sets and test them as separate audiences)
  3. your 30 day page engagement audience (when this is used with Advantage+ Audience, Facebook’s AI goes and finds people similar to those who have recently interacted with your page / ads)
  4. broad targeting (e.g., no targeting at all other than gender / age if you know what specific demo your book appeals to).
    • For romance, select women. Otherwise most authors should just leave the demographic settings untouched during their initial tests to see what the AI finds, then narrow things later during future rounds of audience testing if they want.
    • Note that with Advantage+ Audience, Facebook can ignore the demographic parameters you set here if its targeting AI feels like a different demographic is generating cheaper clicks than the one you specified.
  5. your choice (e.g., movies, TV shows, video games, book blogs, newspapers, Kindle Store, an interest related to your book like dogs if you wrote a book about dogs etc.)
  6. shared audiences (if other authors in your genre have shared their page engagement or pixel audiences with you, these can perform well, since Advantage+ Audience can find similar people)
  7. 1% Lookalike based on your 30 day page engagement (optional, Lookalikes have been declining in usefulness since the Apple iOS 14.5 privacy updates a couple years back)

Best Practices

The best practices here for the ad settings are the same as when you’re testing creatives and running ads normally.

  • Naming Convention(campaign): Campaign Objective / Region: Book Audience Test
    • Ex. 1T/US: SCBOX1 Audience Test = Audience test for the first box set in the Sebastian Clifford series running in the US using the Traffic objective
    • Since this is the first step in the testing chain, it gets called “1T.” Creative testing campaigns use “2T.”
    • If you’re using the tracking sheet in the course, make sure the campaign name includes the objective (T = Traffic, S = Sales) and region (US, UK, DE, CA, or AU) at the start. This allows the spreadsheet’s formulas to read the objective and region.
  • Naming convention (ad set): Audience Type: Name of Audience
    • I = Interest, RT = retargeting audience, LA = Lookalike
      • Ex. I: Lee Child
      • Ex. LA: 1% Page Engagement 365 days
      • Ex. I: Women in US x Reading x UK (the “x” is shorthand for narrowed by; so this is Women in the US narrowed down to only those who are interested in both Reading and the UK as a general topic)
    • Alternatively, you can use Audience Code: Name of Audience.
      • Ex. A100: Popular UK Mystery Authors
      • Ex. A101: Popular UK Mystery Authors x Kindle Store
      • Ex. A106: All UK
  • Naming convention (ad): G100 C100 H100 A100
    • The codes allow you to drill down and analyze the performance of each specific ad component: the image, copy, headline, and audience. I’d only recommend including the audience code when you’re testing audiences, otherwise this will massively multiply the number of links you need to create.
    • Starting the count from 100 instead of 1 makes it much easier to search for your creatives on Facebook / Amazon Attribution.
    • If you’re not using the coded naming convention, just name the ad something descriptive along with the audience (E.g., “Dog in Park Big 6”).
    • Regardless of what naming approach you use, make sure the name of the Facebook Ad matches exactly to the Amazon Attribution link name. This will allow you to easily cross-reference the data and also allow you to tie the ad + attribution data together with spreadsheets (if you so choose).
  • Advantage+ Campaign Budget: turn this on
  • Budget: $5+/day, would recommend higher budgets to get data faster (here $100 NZD = ~$65 US)
  • Region: start by testing audiences in the US, since that will be the main region 99% of authors will be running ads to. You can then take your best US audiences and reuse them in other regions; they tend to transfer over. You don’t need to retest them using this process in other regions, but can do so if you want.
  • Performance Goal: set this to link clicks; this is the default, but sometimes it does landing page views instead, which is ~2x – 4x the cost.
  • Advantage+ Audience (ad set): this is already mandatory on most ad accounts and will be mandatory for all accounts as of January 2024. I would recommend turning it on even if you still have the option to disable it. Testing and gathering data on how the new audiences work will make the transition to the new targeting settings much smoother for you come January.
  • Placements (ad set): News Feed only
  • Multi-advertiser ads (ad): turn this off; it allows your ad to be shown in a “you may also like” style carousel (a la the also boughts on Amazon) below other ads.
  • Standard Enhancements (ad): e.g., music; turn all these off.
  • Optimize Text per Person (ad): turn this off; it can swap the headline and copy or run the ad without a headline / copy, which hurts performance and skews the test data.
  • # of Audiences: can test as many audiences as you want at one time, but more than 5 at once is probably overkill.
    • Each audience should be tested in its own ad set.
    • All the creatives / settings are the same between these ad sets with two differences:
      • 1) the audience
      • 2) the attribution links for the ads in each ad set (you need to use unique attribution links for each ad + audience combo so you can track the performance by specific audience).
  • # of Ads: 1 – 3; if you have more than 1 ad you get a better idea of how that audience performs across multiple different types of creatives. But you have to create more attribution links, since you have to make a specific attribution link for each ad + audience combination. E.g., 3 ads for testing 5 audiences = 15 unique attribution links.
    • For the ad, if you don’t have any winning creatives yet, start with the book cover on the book background with the book blurb. There are exceptions, but if this doesn’t perform well with the audience, then that audience probably isn’t a great match for the book.
    • If you have some winning creatives, take 1 – 3 of your top performing creatives and use them to test the audiences.
    • Use squares (1200 x 1200) for the images; these tend to perform best.


For creative tests, you set the automated rule to turn the ads off at the ad level. However, for audience tests, set the rule at the ad set level.

For audiences, I recommend getting 100 – 500 clicks per audience (for creatives, I recommend 100 clicks). This gives you a larger data sample to determine which audiences are performing best. Since you’ll be reusing the audiences across many different ads, getting more data is worthwhile because you want to be sure that a given audience is effective.

To set a rule:

  • Select all the ad sets in your audience testing campaign
  • Go to Rules > Create a New Rule in the middle of the screen
  • Name: Audience Test – 300 Clicks
  • Action: Turn off ad sets
  • Condition: After link clicks > 300
  • Time range: maximum
  • Schedule: continuously

To make sure the rule is active, select all the ad sets, go to Rules again and then select “View Active Rules.” The rule you just created should show up as active.

If this is your first time using a rule, come back every 12 – 24 hours to see if the rule threshold has been reached (e.g., an ad set has more than 250 clicks) and confirm the rule is triggering correctly. Once you know it’s working, then you don’t have to keep checking on it.

The follow-up with the analysis, how to use the codes, and a Facebook Ads spreadsheet template that ties the attribution data and ad data together to crunch all the key numbers for you are available in Scaling Mastery Pro.