Amazon’s new AI guides know what you want to buy sooner
Amazon is adding AI to a new facet of its online shopping experience with the release of its AI Shopping Guides. The new feature aims to take over the product research part of searching for a product by deploying generative AI models that create personalized companions to your search. You can try it on Amazon’s website and mobile app, but only in the US for now, and view guides for over 100 product categories.
The AI Shopping Guides start with a standard search for an item. In addition to the usual list, you’ll see an AI guide appear if there is one for the category you’re viewing. When you open the manual, you’ll see an AI-curated collection of information about the products, including basic information, charts comparing different specifications, and reviews from previous buyers.
The AI models create guides that analyze all the information Amazon has about the products for sale and how people rate them to write their own descriptions. It will even rewrite the descriptions so you can understand some terms you may not know. The AI will then write custom recommendations for you based on the analysis of both the products and your own search and purchase history. Specifically, using AI to continue scanning product listings means that the AI Shopping Guides stay up to date even as new products are released and old ones are updated or removed.
Rufus signs up
The AI Shopping Guides also complement the Rufus AI chatbot, which Amazon has deployed to provide AI-powered research and recommendations. Rufus makes the AI Shopping Guides interactive by answering follow-up questions you may have, further personalizing your search for a product by, for example, answering a question about two similar products by comparing them not only with each other, but also with products in a similar category that you may have previously purchased.
Rufus also includes some suggestions based less on your history and more on what companies paid to have ads served by the AI. Amazon has also hinted at plans to further personalize its recommendations by using data from Gmail and YouTube (with your permission).
