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FAQPage vs QAPage schema — which should I use?

By Jason Burns, Founder of HurcuLeads · Stuff Doer at Adolicious · Updated

Use FAQPage schema when your site publishes an official multi-question answer page authored by your team, and use QAPage when the page is a single user-submitted question with community-submitted answers — Google's structured-data guides define the two types precisely and enforce the distinction.

FAQPage documentation: a list of Question/Answer pairs authored by the site itself. The type is best-fit for support docs, product FAQs, and educational hubs.

QAPage documentation: a single user-submitted question with one or more community-submitted answers, an accepted answer, and optional suggested answers. Best-fit for forums, community Q&A, and knowledge exchange sites.

Both require answerCount on their Question nodes — a validation failure Google is known to flag. Both are eligible for a rich-result treatment (though FAQ rich results have had visibility constraints in the past; publishers should not deploy either purely for guaranteed visual placement).

The wrong-shape failure mode: an author-written FAQ marked as QAPage validates in the Rich Results Test but misrepresents the page. Match the type to the page's real editorial structure.

For answer engines the practical difference is small — both make the answer text and question text explicit — but honesty matters. Use the type that matches your content.

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Related questions people ask next

  • What is QAPage schema and when should I use it?

    QAPage is a schema.org page type for a page whose primary content is a single user-submitted question with one or more community-submitted answers — use it when the visible page matches that shape, and use FAQPage instead when a single author is publishing an official answer.

  • Does schema.org markup affect AI citations?

    Schema.org markup affects AI citations indirectly but reliably — it collapses the model's attribution problem by making the author, publisher, and answer text machine-readable, and it is the primary signal Google uses to render both classic rich results and the source strip in AI Overviews.

  • What is structured data?

    Structured data is machine-readable metadata added to a web page — typically as JSON-LD in the head — that describes the page's content using a shared vocabulary (schema.org) so search engines and answer engines can understand what the page is about beyond raw text.

  • How do I get cited by Google AI Overviews?

    Get cited by Google AI Overviews the same way you earn any Google organic feature: publish helpful, people-first content on a crawlable, canonical URL with valid structured data, and rank well enough on the underlying query that Google's generative layer pulls your page into the source strip.