AI shopping agents: How Rufus is changing e-commerce
Written by Michael Farr from eKim Commerce
Traditionally, users go to Amazon, search in the search bar and discover a list of products related to their search term.
However, with the growth of AI-powered shopping assistants, the way users search and discover products on marketplaces is set for a dramatic change.
Amazon has recently launched Rufus, it’s AI-powered shopping assistant, with the goal of providing more personalised and informed product recommendations to shoppers.
And with other retailers, including Boots, set to launch similar personalised shopping services in 2025, it’s important that brands ensure their products are discoverable through AI-agents, as user search changes.
This blog looks at what AI-shopping assistants are, how they will change search, and eKim Commerce’s AI-assisted research tool to help sellers get their product content AI ready.
What is an AI-powered shopping assistant?
Found on the Amazon mobile app (in the bottom right), Amazon's Rufus is an AI assistant providing personalised shopping recommendations.
It utilises AI and machine learning algorithms to deliver customised product suggestions based on a conversation to determine a shopper’s preferences, product use case and more.
Rufus gathers data from a variety of sources, including product catalogue, user reviews, and external databases. It uses real-time inputs from websites and social media to keep recommendations relevant.
How will AI shopping assistants change the way we shop for products?
AI-powered shopping assistants move shopping beyond the traditional search bar and results page, to a more tailored experience.
Users can provide a question of their own or selected a question prompted by Rufus. Shoppers then go through a conversational style shopping experience to determine their preferences, product use and personalised recommendation.
To give an example of an experience with Rufus AI, a shopper searching for ‘mens hiking boots’ could see a conversation develop to determine if they are looking for a:
• Summer or winter hiking boot
• Whether ankle support is required
• If insulation is important
• The comfort level of boots based on shopper reviews
• Even if the boot is suitable for wide-feet.
AI and machine learning is used to understand the user’s preference and identify and recommend additional features and considerations that may be useful to the shopper.
Sellers need a new search engine marketing approach
Historically, identifying the most searched keywords in your category, and adding (or ‘stuffing’) these keywords into your content was a sure-fire way to give your product a chance to display in search results.
However, Amazon recognises this shopping experience doesn’t provide the best recommendations for shoppers – and in January 2025 even started to penalise sellers who duplicated keywords in their title.
To optimise your content to be discovered by Rufus AI, it’s crucial for sellers to optimise their product page content (e.g. titles, images, descriptions) with unique product features, seller preferences and key benefits to the shopper.
Brands need to really understand their niche in their category:
• Identify direct competitor products, not just bestsellers
• Understand customer reviews and USPs for their niche
• Communicate these benefits clearly throughout their content
eKim Commerce’s AI research tool can help
eKim Commerce has developed an AI-assisted category research tool to help sellers to review their product category at scale, providing insights and tips to get product content AI ready at scale.
Are you looking to optimise for AI-assisted search? Contact Michael via email: michael@ekimcommerce.co.uk