What Is Schema Markup?

In one sentence

Schema markup is structured data added to a page that states facts about it — price, author, organisation, availability — in a format machines read without interpretation.

What Schema Markup means

Schema is a shared vocabulary (schema.org) expressed in a format, usually JSON-LD, embedded in your page. It declares what a page is about rather than leaving it to be inferred from prose.

It's the only place on a page where you state facts directly. Everything else has to be read, parsed and interpreted, with all the ambiguity that introduces.

Why it matters for AI search

For AI visibility this is disproportionately valuable. A model deciding whether to recommend your product benefits enormously from structured facts it doesn't have to infer from marketing copy.

Accuracy matters more than coverage. Stale prices or overreaching markup can get your structured data ignored entirely, and in some cases treated as manipulative.

See it in action

The same product page, with and without structured data.

Product schema in JSON-LD

Structured data
// click generate

Facts stated, not inferred.

A model reading this knows the price, currency and stock status unambiguously. Reading the prose version, it has to guess — and often guesses wrong or omits you entirely.

How to get it right

Deploying schema properly

  • Start with Organization and WebSite — they're the foundation of entity resolution
  • Add types matching your business model: Product and Offer, Service, Article and Author
  • Wire dynamic fields to live source data so price and availability never go stale
  • Validate after every release, not once at launch
  • Be conservative — markup that misrepresents page content can be treated as manipulative

Common questions

Does our SEO plugin already handle schema?

Partially, and usually inadequately. Most output generic Organization markup with default values nobody reviewed.

The bigger issue is what's missing: Product, Service, author resolution, and sameAs graphs generally need deliberate configuration.

Can incorrect schema hurt us?

Yes. Invalid markup gets ignored, wasting the effort. Markup misrepresenting page content — FAQ schema where no Q&A exists — can be treated as manipulative.

Stale data is the most common practical problem and it erodes trust in all your structured data.

Is schema required for AI citation?

Not strictly — models can read prose. But it substantially improves the reliability of what they extract.

Sites performing well in AI answers almost always have accurate, comprehensive markup. Its absence is a consistent handicap.

These come up alongside Schema Markup constantly.

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