The Peeking Problem That Invalidates Your A-B Tests

Most marketers peek at their A-B test results before the test is finished. Lucas and Luna explain why peeking invalidates your data — even if the sample size looks big enough — and how a simple rule called 'sequential testing' fixes it. They walk through a concrete example: a landing page test at a mid-size SaaS company that would have shipped a losing variant if the team had stopped early. They also discuss how platforms like Optimizely and VWO handle peeking, and why the Bayesian approach isn't a magic bullet. By the end, you'll know why your gut check during week two of an experiment is probably lying to you. #ABTesting #Peeking #SequentialTesting #StatisticalSignificance #CRO #ConversionRateOptimization #DataDrivenMarketing #ExperimentDesign #BayesianInference #Optimizely #VWO #LandingPageOptimization #MarketingMetrics #FrequentistStatistics #SampleSize #FalsePositive #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo