How ChatGPT shopping SEO works
Shoppers increasingly ask assistants what to buy: “best waterproof running jacket under $150” or “a quiet dishwasher for a small kitchen”. ChatGPT shopping SEO makes sure your products are eligible and accurately described when those answers are built. ChatGPT shows product results with images, prices and reviews, drawing on structured product data from merchant feeds and third parties, plus pages it finds through search.
Several inputs matter together. OpenAI’s search crawler, OAI-SearchBot, must be allowed to access your site. Your pages should be indexed in Bing, which supports ChatGPT search. Your product data should be complete, and your products should be discussed in the reviews and buying guides assistants trust. Where OpenAI’s merchant programs are available to you, we prepare your feed for them.
Google AI Mode and the Shopping Graph
Google’s AI shopping experiences, including AI Mode and AI Overviews, draw on the Shopping Graph: Google’s dataset of products, sellers, prices, reviews and availability. It is built from Merchant Center feeds, structured data and the wider web. Products with complete attributes, accurate prices and clear return policies have the best chance of appearing in comparisons and product panels.
Google Merchant Center SEO and feed quality
Product feed optimization is often the fastest win. We fix disapprovals first. Then we rewrite titles around brand, product type and key attributes, fill identifiers such as GTIN and MPN, and add attributes like material, size and color that assistants use to match detailed questions. Shipping and return settings go into Merchant Center too, so delivery and returns information stays accurate.
Product page SEO for AI answers
Product page SEO still matters, because assistants read pages as well as feeds. We add specification tables, sizing and compatibility details, comparison notes and FAQs that answer the questions shoppers ask. That content must be in the initial HTML, since many AI crawlers don’t execute JavaScript.
Structured data that matches reality
We implement Product and Offer markup with price, currency, availability and identifiers, plus MerchantReturnPolicy and shipping details. AggregateRating and Review are added only where real reviews are visible on the page. The markup, the feed and the page must agree. When they don’t, products get disapproved or shown with the wrong price.
Reviews and mentions
Reviews carry a lot of weight in shopping decisions, and in the answers assistants give. We set up post-purchase review collection, connect reviews to Google’s product ratings where eligible, and reach out to the gift guides, review sites and comparison articles that assistants cite in your category.
Perplexity, Gemini and Copilot
ChatGPT and Google get the most attention, but other assistants answer shopping questions too. Perplexity, Gemini and Microsoft Copilot can all recommend products and link to merchants, and each relies on its own mix of search indexes, product data and third-party content. Copilot draws on Bing, so the same Bing indexation work pays off twice. We include these assistants in prompt tracking so you can see where each one sends shoppers.
Who this is for
This service suits stores with a Merchant Center account, or a catalog ready for one, from a few hundred to hundreds of thousands of products. It works best alongside solid technical SEO, since feeds and schema can’t make up for pages that crawlers can’t reach.
Measuring AI shopping visibility
We track a fixed set of shopping prompts across ChatGPT, Google AI Mode, Gemini, Perplexity and Copilot. For each one, we record which products appear, how they’re described and whether prices are right. We combine that with AI referral revenue from analytics. For the wider picture, see our ChatGPT SEO and e-commerce SEO services, or request a free AI visibility audit.