Overview

Amazon has significantly upgraded Rufus, its AI shopping assistant, with persistent account memory, price transparency tools, and activity-based product discovery. The update turns Rufus into a personalized shopping companion that remembers customer preferences across sessions and surfaces products based on lifestyle context rather than keywords alone. With 250 million customers already using Rufus, sellers need to understand how these changes affect product visibility and listing strategy.

What's New in Rufus

• Persistent Account Memory — Rufus now builds running profiles of individual shoppers, retaining details like dietary preferences, hobbies, pet ownership, and household composition across sessions to personalize future recommendations.
• Activity-Based Discovery — Customers can describe situations or upload photos instead of typing keywords. iOS users can even scan handwritten grocery lists to find products.
• Price History and Alerts — Shoppers can view 30-day and 90-day price trends for any product. Prime members can set target prices for auto-purchase with a 24-hour cancellation window.
• Conversational Purchasing — Voice and text-based cart additions, reordering of past purchases, and integrated access to influencer storefronts across more than 35 categories.
• Full-Service Support — Rufus now handles tracking, returns, order modifications, and billing questions, reducing reliance on traditional customer service.

Persistent Memory Changes How Products Get Recommended

The most consequential shift for sellers is that Rufus no longer treats every customer interaction as a blank slate. The assistant now remembers lifestyle details, purchase history, and stated preferences, using that accumulated context to tailor recommendations over time.

This means product suggestions are becoming deeply contextual. A seller offering organic dog treats could see their product recommended to a customer who previously mentioned owning a pet with dietary sensitivities — even if that customer never explicitly searched for dog treats. Listings that describe specific lifestyles and use cases will have a meaningful advantage over generic, keyword-heavy descriptions in this new environment.