The top 3 mistakes that make your A/B test results invalid

Reading Time: 9 minutes A few weeks ago, a Fortune 500 company asked that I review their A/B testing strategy. The results were good, the hypotheses strong, everything seemed to be in order… until I looked at the log of changes in their testing tool. I noticed several blunders: in some experiments, they had adjusted the traffic allocation for the variations mid-experiment; some ...Read the full article