Engine guide: shopping
Shopping assistants do not browse your store like a person. They read feeds, product data and reviews, then match attributes to the shopper's needs.
The short answer
AI shopping assistants recommend products using structured data: merchant feeds, product markup, marketplace listings and review text. Google names Merchant Center feeds and Business Profiles, OpenAI documents a product feed, and Microsoft says feeds, schema and page data should agree. Fill every relevant attribute, keep price and stock current and collect reviews that mention use.
What ranked on 26 September 2026: Commerce blogs and feed-tool vendors dominate. The useful primary sources are the merchant documentation from Google and OpenAI.
Last reviewed · 3 sources
There is no single shopping index. A product can appear in one assistant and not another.
Claim and reality
Flip a card for what is actually true.
Claim
Our descriptions are great, so we will be recommended.
Claim
One feed covers every assistant.
Claim
Star rating is what matters.
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Questions
Nothing in the Google, OpenAI or Microsoft pages I reviewed says merchants can pay for placement in organic results. Label your reports by surface.
For branded products sold by several retailers, yes. Identifiers let assistants match your listing to the same product elsewhere.
Whenever price or stock changes. OpenAI's docs describe daily snapshots after an initial sample.
Evidence, labelled
Each claim is labelled and sourced. Google rows speak only for Google.
Last reviewed · 3 sources
Merchant Center feeds and Business Profiles help products appear in Google AI responses.
Confirmed
Google's guide says so. It guarantees nothing.
OpenAI accepts a structured product feed.
Confirmed
CSV or JSON with identifiers, descriptions, price, inventory, media and fulfilment. Required fields keep price and availability accurate.
Copilot draws on web data and product feeds.
Reported
Microsoft's guide, as reported by Search Engine Journal. Keep feeds, schema and on-page data aligned.
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