Why Your A-B Test Results Disappear After You Ship

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Why Your A-B Test Results Disappear After You Ship

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Episode 34 of Conversion Rate Optimization with Fexingo tackles a painful, rarely discussed failure mode: the winner that vanishes the moment you deploy it. Lucas and Luna dig into the 'novelty effect' and the 'Hawthorne effect' — two behavioural phenomena that inflate A-B test results during the experiment but evaporate once the change becomes permanent. They walk through a real case study from an e-commerce company that saw a 15 percent lift for a redesigned checkout flow during the test, only to see conversion revert to baseline within two weeks of launch. The hosts break down the diagnostic steps CRO teams can take: running longer tests to measure decay rates, building a 'persistence metric' into your testing framework, and differentiating between treatments that work because they're genuinely better versus treatments that work because users are paying attention to something new. If you've ever shipped a winning variant that quietly stopped winning, this episode explains why — and how to stop wasting resources on illusions of improvement. #NoveltyEffect #HawthorneEffect #ABTesting #CRO #ConversionRateOptimization #StatisticalValidity #BehavioralEconomics #ExperimentDesign #PersistenceMetric #DecayRate #Ecommerce #CheckoutOptimization #LandingPageTest #DataReliability #MarketingScience #FexingoBusiness #BusinessPodcast #Business Keep every episode free: buymeacoffee.com/fexingo

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