Structured Data
Machine-readable markup that tells engines what your content means, not just what it says.
What is structured data?
Structured data is machine-readable markup that describes the meaning of a page’s content — its entities, types and relationships — so AI engines and search interpret it explicitly rather than inferring it from prose.
Structured data converts a page from text a machine must interpret into facts a machine can simply read.
Unstructured prose forces an engine to guess: is this an organisation, a product, a definition? Structured data removes the guesswork by attaching explicit types and properties — typically via the schema.org vocabulary, serialised as JSON-LD. The engine reads the labels instead of inferring them, which raises recognition and disambiguation accuracy.
For AEO/GEO, structured data is a primary lever. Marking up FAQs, definitions, breadcrumbs and the brand entity itself makes content easier to retrieve, quote and attribute correctly. It is how a brand asserts, in the machine’s own language, exactly what it is and how its content is organised.
Structured data, the schema.org vocabulary, JSON-LD syntax and FAQ schema form one stack: structured data is the goal, schema.org provides the types, JSON-LD carries them, and FAQPage is a high-value specific case.