Schema markup (structured data in the schema.org format) has long been used to enrich Google search results with rich snippets. What most brands have not realized yet: the same format is also one of the most reliable sources AI engines use to extract precise facts about your business.
Why does AI prefer structured data?
Free-form text on a webpage can be ambiguous, AI has to interpret context, separate opinion from fact, and guess which information is most accurate. Schema markup removes that ambiguity: price, operating hours, rating, address, and business category are all stated explicitly in a format a machine can read directly, with no interpretation needed.
The schema types with the biggest GEO impact
For most brands, four schema types matter most: Organization (basic brand identity and information), Product (product details and specs), FAQPage (frequently asked questions with answers, a format AI loves because it mirrors a Q&A pattern), and Review/AggregateRating (a standardized summary of customer reviews).
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Try it free →Common mistakes that hurt schema effectiveness
The most common one: schema data that is out of sync with the content visible on the page (for example, the price in the schema differs from the displayed price), or schema filled in carelessly without reflecting the actual content. Search engines and AI can detect this mismatch, and it lowers trust in the entire domain, not just that one page.
Where to start
Prioritize the pages with the highest traffic and conversion potential first, usually your main product pages and FAQ page. Use Google's Rich Results Test to validate the implementation before publishing. Fratello includes a schema markup check as part of its technical GEO audit, so a brand knows exactly which pages need fixing.