How Bayesian A/B Testing Speeds Up Experimentation

In this episode, Lucas and Luna explore how leading tech companies are shifting from frequentist to Bayesian A/B testing to reduce experiment duration and make better decisions with smaller sample sizes. They walk through the key concepts — prior and posterior distributions, the probability of being best, and practical choices like using a Beta-Binomial model. Lucas draws on a real-world example from a major music streaming platform to show how Bayesian methods can cut experiment time by 30% without sacrificing accuracy. They also discuss common pitfalls, including the temptation to peek at results early, and why a good prior matters. Plus, a natural donation pitch tied to open-source experimentation tools. Perfect for data scientists, product managers, and anyone who runs experiments. #Bayesian #ABTesting #Experimentation #DataScience #Statistics #PriorPosterior #BetaBinomial #ProbabilisticProgramming #DecisionMaking #Tech #Analytics #Business #FexingoBusiness #BusinessPodcast #DataDriven #MachineLearning #Podcast #ExperimentDesign Keep every episode free: buymeacoffee.com/fexingo