AI visibility for e-commerce: get your products into ChatGPT shopping and AI Mode

They match the shopper's question to structured product data, then use reviews and web pages to decide which products and brands to describe. On ChatGPT, OpenAI says a product appears when ChatGPT judges it relevant to the shopper's intent, and that product results are selected independently, are not ads and are not influenced by OpenAI partnerships.^[1] On Google, AI Mode's shopping features are built on the Shopping Graph, which Google described in May 2025 as more than 50 billion product listings with more than 2 billion refreshed every hour.^[5]

So there are two jobs. First, make your product data complete, accurate and available to each platform. Second, make sure the wider web (reviews, roundups, marketplaces, forums) describes your brand in a way that gets you named for category questions like “best carry-on suitcase under $200” or “vegan running shoes for wide feet”.

OpenAI documents three things merchants can act on: how merchants are ranked, how product data reaches ChatGPT, and what a product feed contains.

• Merchant ranking. When a shopper opens a product, ChatGPT may list merchants that sell it. OpenAI says merchants are ranked on factors such as availability, price, quality and whether the merchant is the maker or primary seller, using metadata from third-party providers or from merchants directly.^[1]
• Getting your catalog in. OpenAI's merchant page invites merchants to apply to share product data, and says Shopify and Etsy catalogs are already integrated without a separate application.^[2]
• Direct product feeds. OpenAI's feed specification lists core fields including a stable item ID, title, description, product URL, brand, seller name, main image, availability and price, with GTIN, MPN, condition and variant fields as optional extras.^[3] OpenAI's commerce docs add that recommended attributes such as rich media, reviews and performance signals improve ranking and relevance.^[4]

Through the same product data that powers Google Shopping: Merchant Center feeds and product structured data on your pages. Google's guidance for AI features says there are no extra requirements to appear in AI Overviews or AI Mode, and recommends keeping your Merchant Center and Business Profile information up to date.^[6] Google's product structured data documentation says that providing both structured data and a Merchant Center feed maximizes eligibility and helps Google verify your data.^[7]

In practice, if your Merchant Center account has disapproved items, missing identifiers or stale prices, fix those first. They affect every Google shopping surface, not just AI Mode.

Start with the fields every platform needs and that shoppers ask about. The same facts should match across your feed, your structured data and the visible product page.

• Write titles a person would search for: “Women's waterproof hiking boot, wide fit” beats an internal SKU name.
• Answer common questions in the description: dimensions, materials, compatibility, care, what is in the box.
• Keep price and stock in sync. OpenAI's feed guidance asks merchants to update the feed when a sale starts or ends.^[3]
• Use real identifiers. Do not invent GTINs.

Use Schema.org Product markup in JSON-LD, with an Offer for price and availability. Schema.org defines Product with properties including brand, gtin, mpn, sku, offers, aggregateRating and review.^[8] Google supports two flavors: product snippets for pages that review products, and merchant listings for pages where the product can be bought.^[7] A minimal merchant listing looks like this:

{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Trail Runner 3 waterproof running shoe",
  "image": "https://example.com/img/trail-runner-3.jpg",
  "description": "Waterproof trail running shoe with a wide toe box.",
  "brand": { "@type": "Brand", "name": "Example Outdoor" },
  "gtin13": "0000000000000",
  "sku": "TR3-BLK-42",
  "offers": {
    "@type": "Offer",
    "url": "https://example.com/trail-runner-3",
    "price": "129.00",
    "priceCurrency": "USD",
    "availability": "https://schema.org/InStock"
  },
  "aggregateRating": { "@type": "AggregateRating", "ratingValue": "4.6", "reviewCount": "212" }
}

Only mark up what is visible on the page and true. Replace the placeholder GTIN with the real one, or leave it out. Validate with Google's Rich Results Test and fix warnings on your best sellers first.

For category questions, assistants can lean on what others say: buying guides, “best of” roundups, review sites, marketplaces and forums. Product feeds tell an engine what you sell; these sources tell it whether you are worth naming. Which sites matter varies by category and country, so measure it instead of guessing.

• Find the cited sources. For each category question, list the domains engines cite. Start with the ones that appear most often.
• Earn editorial coverage on merit. Send samples and clear specs to the reviewers and publications that are already cited. Do not pay for undisclosed placements.
• Keep marketplace listings consistent. If you sell on marketplaces, use the same product names, identifiers and core claims as on your own store.
• Collect reviews where shoppers read them. On your own product pages and on the third-party sites that engines cite for your category.
• Answer real questions. A sizing guide or comparison of your own models can be quoted in answers to specific questions.

Also check that AI search crawlers can reach your product and category pages. A bot-management rule that blocks them can quietly remove you from answers that search the web. The AI crawler checker tests robots.txt and headers for 21 AI bots.

Track a fixed set of unbranded shopping questions per category and market: “best espresso machine under $500”, “sustainable kids' clothing brands”, “where to buy a standing desk in Australia”. Measure how often your brand is named, which competitors appear and which sites are cited, across the engines your customers use. Ask each question in several wordings and over several weeks, because single answers vary a lot.

1. Audit your top 50 products: titles, descriptions, identifiers, price and stock match across feed, markup and page.
2. Fix Merchant Center errors and keep feeds refreshing on price and stock changes.
3. If you are not on Shopify or Etsy, review OpenAI's merchant documentation and decide whether to apply for direct feed access.
4. Add or repair Product and Offer structured data on every product page.
5. List the sites engines cite for your top ten category questions and plan outreach to the ones that skip you.
6. Set a baseline for brand mentions on category questions and re-measure after four to six weeks.

See the e-commerce solution page for example question sets and the Source Map for how cited sites are reported.