--- format: "aidr-story-markdown/v1" id: "0ff719d6f30314f35b9c976749f025f76718a99d180fbd2f1e8d029442c63367" canonical_url: "https://aidr.today/0ff719d6?lang=en" title: "Uplifting conversion across the acquisition funnel with personalization using contextual bandits on AWS" lang: "en" requested_lang: "en" available_langs: ["en","vi"] translation_fallback: null fallback_fields: [] published_at: "2026-10-01T16:51:04.000Z" category: "Models" topics: ["amazon","llm","funding"] source_urls: ["https://aws.amazon.com/blogs/machine-learning/uplifting-conversion-across-the-acquisition-funnel-with-personalization-using-contextual-bandits-on-aws/","https://huggingnews.com/ai/bond-investor-demands-drive-up-ai-data-center-funding-costs-d04471c4","https://marketbrief.now/ai/bond-investor-demands-drive-up-ai-data-center-funding-costs-d04471c4"] summary: "Generative AI makes it cheap to produce personalized content at scale, but which variation do you show each customer? Amazon Payments used a multi-objective contextual bandit on Amazon SageMaker AI to personalize an acquisition funnel, achieving a high single-digit conversion lift for one audience, and learning why content, not the model, was the constraint." --- # Uplifting conversion across the acquisition funnel with personalization using contextual bandits on AWS > [Open the canonical story]() **Published:** 2026-10-01T16:51:04.000Z **Category:** Models **Topics:** amazon, llm, funding ## Summary Generative AI makes it cheap to produce personalized content at scale, but which variation do you show each customer? Amazon Payments used a multi\-objective contextual bandit on Amazon SageMaker AI to personalize an acquisition funnel, achieving a high single\-digit conversion lift for one audience, and learning why content, not the model, was the constraint\. ## Sources - [Story source]() - [Story source]() - [Story source]()