Target Prepares Its Product Search for AI Shopping Agents

Target (https://www.target.com) is adapting product discovery for shoppers who increasingly ask broader, more contextual questions—and for AI agents that may shop on their behalf. At Shoptalk Fall 2025 (https://fall.shoptalk.com/), Ranjeet Bhosale, the retailer’s vice president of digital product management, described generative engine optimization (GEO) as an emerging priority alongside traditional search optimization.

Most Target shoppers still use short, one- or two-keyword searches, Bhosale said. But some are starting to enter longer queries shaped like requests for advice, such as “what’s a good gift for a nine-year-old?” That shift changes what a useful result needs to provide: not just a matching product, but recommendations that reflect the shopper’s wider need.

Bhosale said a search for a summer party could call for tableware, party supplies, grilled meat and sunscreen—not simply a page of tableware. Presenting a broader assortment in a relevant way, he said, can help shoppers understand the options available and find items suited to the occasion.

The shift also has implications for how retailers organize and describe their products. In a generative search experience, an AI system may need to interpret a shopper’s intent, connect it to related categories and explain why particular items fit. Retailers therefore have an interest in making their products understandable not only to people browsing their own sites, but also to AI systems that mediate discovery.

Target is preparing for agent-to-agent interactions in which a shopper uses an external assistant to ask about products, and a Target agent responds. Bhosale said the customer may not visit Target.com directly. In that scenario, GEO means training agents to represent Target’s products effectively, whether the interaction happens through a third-party assistant or an agent built for Target’s own shoppers.

The retailer has already tested generative recommendations through Bullseye Gift Finder, introduced during a previous holiday season. The tool suggested gifts for children based on details including age, hobbies and favorite brands. Bhosale said it saw strong adoption, and Target is considering how to extend the capability to other seasonal occasions, including Valentine’s Day and Mother’s Day.

That reported adoption comes as consumer skepticism remains a barrier to AI shopping assistants, according to studies cited at the event. Bhosale said Target has found that shoppers are willing to use generative AI when its results are relevant and contextual, and when they can trust the recommendations.

For retailers, the practical challenge is broader than adding a chatbot. Search, product information and recommendation systems may need to work across a mix of direct shopping journeys and AI-mediated ones. The quality of an agent’s response will depend on whether it can identify suitable products and present them in context, while maintaining a clear connection between a shopper’s request and the items offered.

Target’s next step is to scale its gift-finding approach beyond the holiday season while preparing its agents for external interactions. How well retailers make product catalogs legible to third-party assistants—and earn shoppers’ confidence in the results—will help determine whether GEO becomes a meaningful part of online merchandising.

Cited: https://www.retaildive.com/news/target-rethinking-search-geo-generative-ai/760537/

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