A/B test Facebook ad interests and behaviors

Contributors

@jiteomaregmail-com


Business Benefits

Improve your ad performance and increase ROI on ad spend.


Leave Age and Gender open-ended in your regular campaign setup until you gather enough data from your ad reports to determine what audience age and gender combinations work the best.

Assuming the age and gender of your audience can actually hurt your campaign’s performance and cost you conversions.

Ask your sales team, customer success, and marketing teams to describe your target audience, including interests and behaviors, and add this to an Audience document.

If you already have the audience you want to test in mind, document that instead.

Go to Facebook Ads Manager, select the campaign or ad set you set up without interest and gender, and click on A/B Test in the menu bar.

Select Custom as your variable and click on next.

Enter your ad test name, budget, schedule - at least 72 hours - and select a metric that you’ll use to gauge success.

Choosing one primary metric gives you a single measure of performance to use as a basis for your A/B testing. For example, if your goal is to see which audience costs more to market to or who clicks on your ad, focus on CPC.

Click on Review to open the settings for the duplicated campaign or ad set.

Because you chose Custom as your variable, Facebook will duplicate your campaign or ad set.

Change the name of the duplicated ad set/campaign, leave other settings the same, but change the audience to the one described in the target audience document you created earlier.

Check that your ads and identity (Facebook page) are the same and publish the changes.

Run ads for at least 72 hours without making any changes to give the Facebook algorithm enough time to optimize.

72 hours is the minimum you should run your test for. If you don’t have a statistically significant results after 72 hours, continue to run the test.

Once you identify your best audiences, if you have any that are particularly large (>10 million), consider splitting them out into separate ad sets to identify top performers within your groups.

Splitting a winning ad set into 2 separate ad sets and adding half of the interest group into each ad set will allow you to find the best performing interests within the larger groups that you tested originally.