Product Recommendation in Agentic Search

Agentic search is changing how products are discovered. Instead of browsing pages of results, shoppers now receive a small set of product recommendations, often just a handful per query.  

That shift makes visibility binary: your product is either included, or it’s not.

This white paper breaks down how product recommendation actually works in agentic search, and what determines whether a product is retrieved and recommended. It introduces the two stages that define performance:

• Selection — whether your product is retrieved into the consideration set
• Ranking — whether it’s trusted enough to be recommended

Most products fail during selection, before ranking is even evaluated.

Inside, you’ll learn:

• Why category alignment is the biggest driver of product retrieval
• How missing or incomplete attributes prevent products from being considered
• Why prompt tracking doesn’t explain (or improve) recommendation performance
• How models interpret categories differently than the retail shelf
• What signals actually determine whether a product is recommended

The takeaway: product recommendation, not brand visibility, is what determines success in agentic search.

And that starts with how clearly your product is structured, categorized, and understood.

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