A/B testing (or split testing) involves running two or more variations of an ad — different images, headlines, or audiences — against each other to see which performs better, based on real data rather than guesswork. This lesson covers how to set up a proper A/B test using Meta’s built-in testing tool, ensuring only one variable is changed at a time (like just the image, keeping copy and audience the same) so you can clearly identify what’s actually driving the difference in performance.