Structured data (schema)
Structured data is standardized markup, usually schema.org in JSON-LD, that labels a page's content so search and answer engines can understand and reuse it.
Structured data is standardized markup that labels the meaning of a page’s content — this is a product, that is its price, this is a review score — so machines can understand it without guessing. It usually follows the schema.org vocabulary in the JSON-LD format, and it powers rich results in search and helps answer engines extract facts cleanly.
How it works
You add a JSON-LD block that describes the page as a typed entity (Product, Article, FAQPage, Organization, DefinedTerm) with named properties. Search engines validate the markup and may use it to render rich results — star ratings, prices, FAQs, breadcrumbs — and to reinforce their understanding of the entities involved. Structured data does not directly raise rankings, but the rich results it unlocks lift click-through rate, and the entity clarity it provides helps both traditional and AI systems trust and reuse your content. The markup must reflect content actually visible on the page.
Where it applies
Any page with facts worth labeling:
- Ecommerce — Product, Offer, and Review markup for rich shopping results.
- Publishing — Article, Author, and FAQ markup for eligibility in enhanced results.
- Local — LocalBusiness and organization data for maps and knowledge panels.
- B2B and SaaS — FAQ and HowTo markup that answer engines lift into responses.
What matters from each seat
- In-house — prioritize the schema types that earn rich results for your templates, and validate them at scale.
- Engineering — generate JSON-LD from the same data that renders the page, so markup and content never drift.
- Editorial — write genuine FAQs and definitions worth marking up, since schema on thin content earns nothing.
- Agency and consulting — a schema coverage audit maps quick rich-result and AEO wins across a site.
From the field
Modernizing schema and structured data was a foundational part of rebuilding a baby-registry brand for AI ingestion. Clean, accurate markup is what lets an answer engine understand your entities and reuse your facts confidently — unglamorous plumbing that quietly decides whether the machine trusts your content.
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