Traditional A/B testing often relies on fixed sample sizes and can be time-consuming. Bayesian A/B testing, on the other hand, allows for dynamic updates and quicker decision-making. By continuously updating the probabilities as new data comes in, marketers can determine which version of an email performs better without waiting for the entire testing period to conclude.