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Shoppers ask AI engines for product recommendations (“best running shoes for flat feet under 150”) and Google shows AI Overviews above search results. Across five e-commerce verticals, Reddit and YouTube appeared in AI citations in every one, next to brand product pages, marketplaces and review media.

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Set up

  • Engines. Commerce brands get Google AI Overview by default, so keep it on next to the chat engines.
  • Prompts. Track product-level questions with real constraints, such as budget, use case, size or location.
  • Competitors. Track brands rather than retailers, and add product line names as synonyms.
  • Languages. Add every market you sell in, as described in Languages.

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What to work on

  • Shelf space usually has the most impact, because review sites, “best of” lists, Reddit threads and YouTube reviews shape most product recommendations. You can work them in Shelf space.
  • Product and category pages should state the facts engines compare: price, materials, sizes and ratings. Make sure assistants can fetch them by checking Cited in answer on the AI traffic page.
  • Buying guides work well when you write them with the GEO writer in the listicle or comparison format.

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Metrics to watch

  • Mention rate and position per engine, especially Google AI Overview.
  • Performance by language for each market.
  • AI referrals reaching checkout, which you can track by adding /checkout as a Conversion path.
ChatGPT and Google also show product cards and shopping ads inside AI answers, but Notra tracks only the answer text and its citations and ignores those product cards and ads.
Last modified on October 8, 2026