Bayesian A/B testing

Bayesian A/B testing is a method to compare two options (like webpage designs) by updating beliefs about which is better as new data comes in. Instead of treating the results as fixed once the test ends, it continuously adjusts the probability that each option is superior, based on observed user behavior. This approach provides a clear measure of confidence in the choice and allows decision-makers to act sooner if one option clearly outperforms the other. It offers a flexible, intuitive way to make data-driven decisions, incorporating uncertainty and updating as more information becomes available.