Generative AI has made it possible to produce large amounts of personalized content quickly and at low cost. In our previous post, we showed how generative AI on Amazon Bedrock can produce personalized content at scale while staying within brand guidelines and guardrails. The new challenge is now one of selection. Among all of those options, which one do you show each customer, and how long does it take to learn the answer? This post tackles the selection challenge that follows the proliferation.
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. The problem turned out to be the content, not the model. We cover the…
