What is structured data?

Structured data is standardized markup — most commonly JSON-LD using the schema.org vocabulary — added to a page's code that explicitly labels what its content means. Instead of leaving a search engine or AI system to guess that "$49.99" is a price or that "Jane Ortiz" is an author's name, structured data states it directly in a machine-readable format.

Why it matters

Without structured data, a search engine or AI model has to infer meaning from formatting, position on the page, or surrounding text — a process that's error-prone and inconsistent across templates. Structured data removes that guesswork by attaching an explicit label to each fact.

A concrete example

An Article schema block on a blog post can explicitly state the headline, author, and publish date as separate, tagged fields. Both Google and an AI citation system can then extract those three facts reliably, rather than trying to parse them out of headline text, byline formatting, or a date string buried in the footer. That reliability is what makes structured data useful for search results features and for AI systems deciding what to cite.

Going deeper

Structured data covers far more than articles — products, reviews, events, FAQs, and organizations each have their own schema.org types with specific required and recommended fields. For a hands-on walkthrough of writing and validating JSON-LD, see the structured data SEO guide. Structured data is also one of the main ways sites feed information into a search engine's knowledge graph — see the knowledge graph glossary entry for how that connection works.

What Is Structured Data? A Quick Definition