Obliterate Facebook Targeting Overlap! | Step-by-Step Guide To Ditch Audience Duplication

Two large eyes pear through the outlines of human heads to introduce our post.

You run a lot of Facebook ad campaigns, and you’re dang good at it.

You’re mastering the art of audience intake, taking advantage of financial targeting segments, and implementing killer retargeting strategies.

Great job! Seriously.

Have you ever thought about advertising oversaturation, cannibalization, and general ad fatigue as byproducts of audience overlap?

There’s nothing to be ashamed of. It happens to the best of us.

The better of the best of us do something about it. We take it upon ourselves to investigate, review, and improve ad targeting. We continue to scroll through this post and gain knowledge.

Audience overlap, oofta 

What is it?
Targeting the same users in multiple audiences/groups/ad sets, potentially at the same time.

This may lead to quicker ad/brand fatigue, poor in-channel & down-stream performance, inflated costs, and a less-than-desireable overall user experience.

How does it happen?
Overlap may occur after building out multiple campaigns/ad sets that target individuals with similar (or the same) psychographic characteristics, or even using the same audience in multiple campaigns without assessing the characteristics and effects of intersection and overlap.

Always question your targeting. Nothing is ever perfect, but never stop striving for the optimal audience.

Why does it matter?!
It can:

  • frustrate viewers with frequently over-served ads
  • lead to inflated costs, as poor click-through rates affect relevancy score and lead to an increased cost per click. If they’ve already seen and passed on your ad an hour ago, odds aren’t great right now. Two separate (and technically competing) ad sets targeting the same individual doesn’t know that.
  • muddy back-end data. Clean, unique audience segmentation (along with properly tagging elements of audience makeup) is key to knowing how and who interacts with your product or site post-click. Improve your data confidence score by limiting the number of audience pools any given individual may be a part of, and therefore showing up in on the back-end.

Steps to combat audience overlap

Step I: Audit current campaigns, self-assess audiences

First, map out your current and recent audiences. Outline and categorize audiences by various attributes, including but not limited to:

  • Base saved audiences
  • Age
  • Gender
  • Location
  • Psychographic targeting
    • Interest
    • Demographic
    • Behavior
  • Device splits
  • Current exclusions

With these simple, core elements of campaigns laid out, look for overlap. Prioritize obvious red flags first, followed by groups that may include the same individuals, and finally, review least suspicious audiences last. How? By utilizing Facebook’s “Audience Overlap” tool. This handy — and fairly hidden — feature allows shrewd social savants to compare percentage of overlap between any two audiences.

Here’s how to find it:
1. Navigate to the audience section of your ads account by selecting “Audiences” from the upper left corner dropdown menu:

Once you're in Facebook Ads click, "All Tools" and then, "Audiences."

2. Find the saved audiences you’d like to compare, check their respective left column boxes, find the “actions” dropdown menu, and select “Show Audience Overlap”:

Select two audience names and click, "Actions" then "Show Audience Overlap."

3. Toggle the primary audience in question, and review the percentage of overlap between it and any other audience:

Next, you'll see the selected audiences overlap. Here 12% of the audiences are the same 33,930 users.

In the above example, you’ll see that 33,000 people were found in both the selected “various media roles” audience and “digital advertising” audience, which was 12 percent of the “various media roles” audience.

Then decide what types of audience composition are most valuable.

Do specific interest, behavior, or demographic elements define your “perfect target”? Use them as a base feature in all audiences, with psychographic variations as subset differentiators.

Is your business location-specific and neighborhood-focused? Prioritize audience proximity. Segment audiences (by distance from your business) into varying radii, excluding preceding rings from any given group.

Finally, as you’ll see in step 2, don’t forget to adjust budget allocation accordingly!

Step II: Take action!

Evaluate (and possibly rank) audiences by campaign-specific value, while keeping size and sales funnel location top-of-mind.

Based on these rankings, decide which audiences will keep overlapping segments of available targets, and get your exclusion on!

A key component of optimal audience segmentation, the art and intricacy of focused exclusions may be an afterthought. Underthinking it, combined with broad strokes of exclusion, may significantly and negatively affect true audience size.

Let’s say you have three audiences with sizable overlap (as illustrated below). If each audience includes exclusions of the other two audiences, you may quickly, easily and unintentionally prohibit ads from serving to a significant portion of your total target.

Venn diagram of 80% of more audience overlap.


  • Audience 1 (A1) excludes Audience 2 (A2) and 3 (A3)
  • Audience 2 (A2) excludes Audience 1 (A1) and 3 (A3)
  • Audience 3 (A3) excludes Audience 1 (A1) and 2 (A2)

What remains (light blue portions) are rather small slivers of the total audience. To combat, allow select audiences to “take” portions of overlap by limiting exclusions:

Same Venn diagram but Audiences have different color codes to show saturation of the ads.

After a few changes to audience exclusions:

  • Audience 1 (A1) excludes Audience 2 (A2) and 3 (A3)
  • Audience 2 (A2) excludes nothing
  • Audience 3 (A3) excludes Audience 2 (A2)

We are left with complete coverage. Good job, you!

By refining audience overlap, you will better prevent oversaturation of ads in users’ feeds and decrease the likelihood of ads over-serving. If you’re promoting different ads to the same audience and knowingly don’t care about over-serving or are striving for same-user conversions, feel free to loosen exclusion restrictions.

Don’t forget to review post-exclusion audience value and size before jumping into final budget allocation. If audience-to-audience value is relatively equal, one recommended, initial way to divide budget is by mirroring percentage of total audience.

Table to remind readers to adjust the budgets between three campaigns based on the number of users in each.

When breaking budgets down by audience/ad set, keep additional segments — like placement (mobile vs desktop), device, age, gender, etc. — in mind. The more ads sets are broken down on the ad set level, the more segmented and reduced budgets will be.

That isn’t to say “don’t segment at the ad set level.” On the contrary, there are perfectly good reasons to do so, including better control over what budget is spent where and the ability to pass through psychographic markers via UTM tags (to better observe segmented post-click user experience).

[Mobile v Desktop] To those who frequently break out ad sets by placement, keep the this top-of-mind: placement segmentation may result in serving to the same audience — once on mobile, once on desktop. Monitoring tips found in step 3 (i.e. keep reading).

Step III: Actively review key metrics to assess overlap

With audiences and budgets in place, launch your campaigns!

Track performance as you normally would and improve overlap assessment by looking at the following:

1. Frequency & Reach

A table of frequency, reach and impressions so Mobile, Desktop, Combined.

If combined frequency is greater than that of segmented ad sets, overlap is occurring. To better understand how much overlap, review the metrics used in calculating frequency: impressions and reach (Data Insider Insight:frequency is calculated by dividing impressions by reach. #TheMoreYouKnow).

In the above example, if mobile and desktop were serving to two independent audiences, we would easily combine their reach totals (198,581) to find total reach. The amount of mobile and desktop overlap is the difference between this and the combined reach stated (182,823), which is 15,758 (8.6 percent total audience).

Monitor this metric moving forward and start setting unique, campaign-specific thresholds for acceptable amounts.


While active comment moderation on paid social ads is always recommended, take the opportunity to get a read on your audience as well. If you observe a disproportionate amount of comments associated with oversaturation —you know, “Stop showing me this!!!” type of stuff — a mental red flag should be raised.

3. Negative Feedback*

Comment moderation only allows you to review messages left. What about the actions taken to remove the ad from a user’s feed? For that, look for the “Negative Feedback” metric in-channel at the ad level to decipher whether ads are leading people to hide or not see your ads. Here, ads are scored as having “low”, “medium”, or “high” negative feedback. While vague and nondescript, the descriptors are better than nothing (we think).

*While negative feedback can’t be directly connected to audience overlap, it’s another potentially valuable view into audience mindset and indicator of potential advertising oversaturation.

Step IV: Refine, combine and improve audiences

For the love of (positive) user experience, take what you’ve learned through step 3 and use it to shape, tweak and better ad delivery.

Re-assess your base audiences and targeting, adjust who’s getting the common/overlap portion of audiences, analyze group performance against account or campaign KPIs, continue to test, and fight the never-ending battle against complacency.

Happy targeting!

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