Uplifting conversion across the acquisition funnel with personalization using contextual bandits on AWS
Uplifting conversion across the acquisition funnel with personalization using contextual bandits on AWS
In this post, we share how Amazon Payments applied AI-based personalization to a product acquisition funnel, using a multi-objective contextual multi-armed bandit (MAB) on Amazon SageMaker AI. In a seven-week online A/B test we currently see a high single-digit percentage relative lift in final-funnel conversion for one customer population, while another saw no improvement over the existing experience.
Selection record
Not admittedSum of both 67 < twice the threshold 120
- Source tier
- Official, first-hand; this tier's threshold is 60
- Pre-filter
- passed：正文详述生成式AI个性化与上下文老虎机模型
A model scores each item twice, independently, against one written standard, out of 100. An item is admitted only when the two scores add up to twice the threshold. The threshold is set per source tier.
Source: AWS Machine Learning Blog · aws.amazon.com