# Schema Markup

## Quick answer

Schema markup is structured data, usually written as JSON-LD, added to a web page's code to label what a piece of content actually is (a product, a price, a review, an FAQ) in a format machines can parse directly, rather than requiring a search engine or AI crawler to infer it from plain text.

## Why it matters

An AI engine that reads a page still has to parse ordinary prose to figure out what's a price, what's a review and what's a direct answer to a question; structured data removes that guesswork. Pages with clear schema markup are easier for both classic search and AI crawlers to summarize accurately, which matters when the summary is what a buyer actually reads instead of the page itself. Markup also has to match what is visible on the page. Structured data that disagrees with the visible content, such as a price in the markup that differs from the price on screen, can cause a crawler to distrust the page or skip the markup altogether.

## How to measure it

Check specific pages (pricing, FAQ, comparison pages) against a JSON-LD validator to confirm the markup is present and error-free, then track whether those same pages later show up correctly summarized in AI answers for related questions. Markup alone doesn't guarantee a citation; it only removes one obstacle to an accurate one, so pair the validator check with an actual read of what AI engines currently say. Re-run the validator after every template change, because a redesign can silently drop the markup from every page that uses the template. A spot-check of a few key pages after each release catches that early.

## Example

A company's pricing page lists three plans in a visual table but has no structured data behind it. An AI engine summarizing the page picks the wrong number because it had to guess from the surrounding text, and the error persists until the company adds markup the engine can read directly instead of inferring from layout, at which point the next AI answer about the same page gets the number right.

## FAQ

### Does schema markup guarantee an AI citation?

No. It makes a page easier to parse correctly, which helps an AI engine summarize it accurately, but the engine still chooses which sources to cite for a given answer out of everything it reads.

### Which pages benefit most from schema markup?

Pricing, FAQ, comparison and review pages benefit most, since those are exactly the page types an AI engine is trying to extract a specific fact from, such as a price or a direct answer.

### Is schema markup only for Google?

No. It's a web standard that any crawler, including the bots AI companies use to read and train on web content, can read the same way.

### How much effort does adding schema markup take?

For a handful of key pages, usually a small, one-time implementation task; the ongoing work is keeping the markup accurate as the underlying page content changes.

## Related terms

- /glossary/ai-crawlers
- /glossary/crawl-budget
- /glossary/llms-full-txt

## Related

- Schema markup and AEO: /blog/schema-markup-and-aeo
- GEO audit tool: /tools/geo-audit