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Summary
Random controlled experiments for A/B testing help improve things like a company's marketing or customer service. However, individually optimizing interventions may not always capture interactions across the entire purchase decision journey. To optimize interventions more holistically, use a Bayesian reinforcement learning model. It can integrate multiple historical experiments, which can improve both current impact as well as future learning.
