How Amazon Payments uses contextual multi-armed bandits on Amazon SageMaker AI to improve acquisition funnel conversion
Uplifting conversion across the acquisition funnel with personalization using contextual bandits on AWS
What happened
Amazon Payments used a multi-objective contextual multi-armed bandit (LinUCB) on Amazon SageMaker AI to personalize content in its product-acquisition funnel. In a seven-week online A/B test, one audience segment achieved a high-single-digit relative increase in final funnel conversion, while another showed no improvement. The team ran one LinUCB model for each stage—application start, submission, and approval—and linearly combined their UCB scores to optimize the full funnel. It open-sourced a repository that can be tried with synthetic data.
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