How should product feeds be structured for AI shopping agents?
AI shopping agents do not browse your store the way people do. They read your product feed first and your pages second, and they decide in milliseconds whether your products are worth recommending. A feed built for humans, vague titles, missing attributes, stale availability, is invisible to the agents doing the shopping.
Agents read feeds before they read pages
When a shopper asks an agent to find running shoes under $120, the agent does not lovingly browse your collection pages. It queries structured data: your product feed, your schema markup, and whatever catalog APIs it can reach. The feed is the menu the agent orders from, and items missing from the menu do not get ordered.
This flips the usual priority. Merchants obsess over page design while their feed titles say things like Summer Fun Top Blue. An agent comparing ten stores will pick the one whose feed answers its questions directly: what is it, what size, what material, is it in stock, what does it cost landed. Design wins the human; data wins the agent.
Write titles and descriptions for machines
Feed titles should be specific and attribute-rich: the product type, key attributes, and variant, in a consistent order. Men's Merino Wool Crew Socks, Charcoal, Large beats Cozy Socks V2 every time for an agent trying to match a request. Put the words a shopper would say out loud near the front of the title.
Descriptions should state facts before story. Material, dimensions, care, compatibility, and what's in the box belong in the first sentences, because agents weigh early structured text more heavily. Marketing copy still matters for the humans who read the final recommendation, but it should follow the facts, not replace them.
Structured attributes beat clever prose
Every attribute you provide as a real field, GTIN, brand, size, color, material, age group, is an attribute the agent can filter on with certainty. The same information buried in a paragraph is a guess. Agents prefer certainty, and when two products are otherwise equal, the one with complete structured data wins the recommendation.
Audit your feed for empty fields the way you would audit for broken images. Size and color variants need distinct, accurate attributes per variant, not one generic row. If your catalog platform supports custom fields for the attributes shoppers actually filter by, waterproof rating, inseam, thread count, fill them. This is unglamorous work with direct revenue impact.
Availability and price must be accurate
Nothing burns agent trust faster than recommending a product that is out of stock or mispriced. Agents remember which merchants waste their user's time, and the better agent platforms track merchant reliability. A feed that updates inventory hourly will outperform an identical feed updated weekly, because the agent can act on it with confidence.
Price accuracy includes the landed cost where you can provide it: shipping and tax estimates that match what the checkout shows. Agents that complete purchases compare the feed price against the checkout total, and discrepancies get flagged. Treat the feed as a promise and the checkout as the moment the promise is kept.
Make policies machine-readable
Agents need your shipping, return, and warranty policies as structured data, not as a PDF linked in the footer. Use schema markup for return policies and shipping details, and keep the feed's policy fields current. An agent asked to find a gift with free returns will filter out every store whose return policy it cannot parse.
This is also where honesty compounds. A clear 30-day return policy stated in structured data beats a vague satisfaction guarantee buried in prose. Agents surface the concrete terms to the shopper before purchase, which means clear policies do not just win agent recommendations, they reduce the returns those recommendations generate.
The takeaway
Agentic commerce rewards the merchants who treat product data as a sales channel, not a chore. Clean titles, complete attributes, accurate availability, honest pricing, and machine-readable policies are the new shelf placement. The stores that invest in feed quality now will be the default recommendations later, while everyone else wonders why the agents never mention them.