Best Practices for A/B Testing

A/B Testing compares different versions of your ads so you can see what works best and use that to improve future campaigns.
 

These are best practices for Facebook A/B Testing:
 

  • Test only one variable for more conclusive results

You will have more conclusive results for your test if your ad sets are identical except for the variable that you're testing.

  • Focus on a measurable hypothesis

Once you figure out what you want to test, create a testable hypothesis that enables you to improve future campaigns. For example, you might start with a general question like, "Do I get better results when I change my delivery optimization?" This can be refined to something more specific, like "Do I get a lower cost per result when I optimize for link clicks or landing page views?" From there, you can set a specific hypothesis, like "My cost per result will be lower when I optimize for landing page views." 

  • Use an ideal audience for the test

Your audience should be broad enough to support your test. Also, you shouldn't use this audience for any other campaigns that you're running at the same time.
Overlapping audiences may result in delivery problems and contaminate test results.

  • Use an ideal time frame

For the most reliable results, a minimum of 7-day tests is recommended. A/B Tests can only be run for a maximum of 30 days, but tests shorter than 7 days may produce inconclusive results.
Your ideal testing time frame may also depend on your objective and business vertical. For example, if you know your typical customer takes more than 7 days to convert after seeing an ad, you'd want to run your test for a longer period of time (such as 10 days) to allow enough time for these expected typical conversions to occur.

  • Set an ideal budget for your test
           Your test should have a budget that will produce enough results to confidently determine a winning strategy.