Bayesian UX testing: A clearer way to interpret A/B test results

Bayesian testing is gaining traction as a smarter alternative to p-value analysis in A/B and multivariate UX tests. Unlike p-values, Bayesian results express probabilities like P(B > A) = 99.8%, making them easier to act on without waiting for fixed sample sizes. Two real checkout and CTA examples show how designers can peek at results early and ship with confidence.