What makes it a test, not a guess
A valid A/B test needs three things: exactly one variable changed, an even and non-overlapping audience split so no one sees both versions, and enough volume for the result to be stable rather than noise. Miss any one of them and the outcome is not attributable to the change you made.
The mistake that isn't a test
On Meta, running two ad sets in one campaign feels like a split test but is not one. The system does not split the audience evenly; it skews delivery and budget toward the early front-runner, and Advantage+ campaign budget makes that worse by actively moving budget to the leader. The clean method is the platform's built-in A/B Test tool, which enforces the random, non-overlapping split. We work through it in why two ad sets in one campaign is not an A/B test. And whatever the split, judge it on volume, not an early conversion rate, and wait out the learning period before you read the result.
Common questions
What is an A/B test in advertising?
A controlled comparison of two versions that differ by a single variable, run on an evenly split, non-overlapping audience, to determine which performs better. The control on the split is what separates a test from a guess.
Why isn't running two ad sets an A/B test?
Because platforms like Meta do not split the audience evenly across ad sets in the same campaign. They skew delivery and budget toward whichever performs better early, so the other version is throttled before it gathers a fair sample. Use the dedicated A/B Test tool instead.