About A/B testing

A/B testing lets you compare two versions of an ad strategy by changing variables such as ad images, ad text, audience or placement. We show each version to a segment of your audience and ensure that nobody sees both, then determine which version performs best.

Before you select a variable to test, choose a hypothesis for your test. For example, you might hypothesise that a Custom Audience strategy will outperform an interest-based audience strategy for your business.

To create an A/B test, you can either duplicate an existing campaign, ad set or ad and change a variable or compare two existing campaigns or ad sets. If you choose to duplicate an existing campaign, we also duplicate your ad budget. Otherwise, we use your current ad budgets, which you can change in Meta Ads Manager at the ad set level. We recommend using the same budget for both versions in a test to ensure a fair comparison. A/B testing can then measure the performance of each strategy on a cost per result basis or cost per conversion lift basis.

We recommend A/B testing when you're trying to measure changes to your advertising or quickly compare two strategies. We do not recommend testing informally, such as by turning ad sets or campaigns on and off manually. This can lead to inefficient ad delivery and unreliable test results. For example, A/B testing helps ensure that your audiences will be evenly split and statistically comparable, while informal testing can lead to overlapping audiences.

You can create an A/B test in Ads Manager or in the Experiments tool. Learn more about the ways to create an A/B test.