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.
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