GPyOpt employs Bayesian Optimization to find the optimal parameters for your email campaigns. It models the unknown function (e.g., the conversion rate as a function of various email elements) with a Gaussian Process and iteratively updates this model based on new data. This allows the algorithm to intelligently choose the next set of parameters to evaluate, making the process more efficient than traditional A/B testing.