Why Your A-B Test Peeking Kills Statistical Validity

Episode 15 of Conversion Rate Optimization with Fexingo digs into the peeking problem — the most common practical mistake in A/B testing. Lucas and Luna use a concrete example from a mid-size e-commerce company to show exactly how peeking at results too early inflates false-positive rates and wastes months of testing effort. They explain the concept of sequential testing and why tools like Optimizely now warn you to stop peeking. The conversation covers the math behind false discovery rates, why 'p-hacking' by peeking is so tempting, and a simple rule of thumb: never check your test before it reaches the pre-determined sample size. Perfect for marketers and product managers who want trustworthy test results. #ABTesting #PeekingProblem #StatisticalValidity #CRO #ConversionRateOptimization #FalsePositive #SequentialTesting #PValue #SampleSize #MarketingAnalytics #ExperimentDesign #DataScience #EcommerceTesting #Optimizely #P-Hacking #FexingoBusiness #BusinessPodcast #Marketing Keep every episode free: buymeacoffee.com/fexingo