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Why Hypothesis Matters in Facebook A/B Testing

To run a good experiment on Facebook, you should first come up with a question, or hypothesis, that you want to test. The hypothesis should be clear, able to be tested, and connected to your business goals.

For example, if you want to know which ad format will work best with your audience in an upcoming ad campaign, a good hypothesis might be:

"A video format works better than a carousel format when I want to tell my audience about new products."

This theory makes sense because:

  • It turns a complicated business goal, like getting more people to think about a new product, into a specific question that can be answered directly by comparing the two ad formats to prove or disprove the statement.

  • There is a test that can give a good answer, in this case an A/B test.

  • It can be answered with metrics that are specific to the test, like how many clicks each ad gets for the same number of impressions.

  • If you do things to test this theory, you can learn more about how well your ads work with your audience

When running tests to learn about the more complicated effects of your advertising, like incremental lift, you can use tools like Experiments to give specific, actionable answers to questions you've already thought of about your advertising.

Taking a data-driven, test-and-learn approach to advertising can help you figure out how your ads are making a difference. Find out more.

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