In A/B testing, a test result that incorrectly shows a difference in test results, or that the winning variant outperforms the other versions, when this fact is not actually the case.

According to some marketing research, about 80% of A/B tests run actually achieve false positive results -- making it important to conduct A/A testing first to verify the test set-up is done correctly.