Why Your A-B Test Needs a Minimum Detectable Effect

Most A-B tests are designed to detect a 10% or 20% lift — but what happens when the true effect is only 3%? In this episode, Lucas and Luna break down the concept of Minimum Detectable Effect (MDE) and why ignoring it leads to false negatives and wasted traffic. They walk through a real example from an e-commerce checkout flow where a properly sized test uncovered a 4% gain that an underpowered test would have missed. Learn how to set realistic MDEs, calculate sample sizes, and avoid the biggest trap in conversion rate optimization: testing for effects too small to measure with your current traffic. If you're running A-B tests without thinking about statistical power, this episode will change how you design every experiment. #MinimumDetectableEffect #ABTesting #SampleSize #StatisticalPower #CRO #ConversionRateOptimization #Marketing #Experimentation #FalseNegative #Ecommerce #CheckoutOptimization #DataDriven #Business #FexingoBusiness #BusinessPodcast #LucasAndLuna #Podcast #MarketingScience Keep every episode free: buymeacoffee.com/fexingo