A/B TESTING MISTAKES I LEARNED THE HARD WAY

Summary from the TLDR Design newsletter

A good A/B test hypothesis should be clear and targeted, with results analyzed by relevant user segments to uncover insights. To ensure accuracy, filter out ineligible users, stick to the calculated test duration, conduct phased rollouts to avoid bias, and monitor counter metrics for unintended effects.