FAQPage schema
A specific schema.org type that declares a page contains a list of question-and-answer pairs, optimized for structured ingestion by search and AI systems.
FAQPage is a schema.org type introduced in 2014 and heavily used since Google's 2019 rich-result rollout. The structure is straightforward: a page-level `FAQPage` object contains a `mainEntity` array of `Question` objects, each with an `acceptedAnswer` of type `Answer`.
FAQPage schema is the single highest-hit-rate structured data type for AI citation across every major answer engine in our data. The explanation is simple: it pre-structures content into exactly the query-answer shape that LLM training and retrieval both favor.
Best practices: the content declared in the schema must also appear visibly on the page (models and Google both penalize hidden schema content), answers should be 40–120 words, and the questions should match real user phrasing rather than marketing-flavored questions.
In AIRRNK
AIRRNK flags every page that has a buyer-intent question block but no FAQPage schema, suggests exact markup, and can inject the schema via the WordPress or Shopify integrations.
- Schema Markup
Structured data embedded in a page (usually as JSON-LD) that describes what the page is about in a machine-readable vocabulary defined at schema.org.
- AI Score
AIRRNK's 0–100 grade for how likely a site is to be cited by a language model, calculated from 47 weighted checks across four pillars.
- Generative Engine Optimization
The practice of making a website more likely to be cited by AI answer engines (ChatGPT, Claude, Perplexity, Google AI Mode) rather than simply ranked on a traditional search results page.
Written by
The AIRank Editorial Team
Research & editorial, AIRank
The AIRank editorial team runs the 47-point scanner, the Observer pings, and the GEO research programme every week. Writing is reviewed by the core engineers who build the Injector, Blaster, and Surgeon agents.
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