What is Structured data (schema)?
Machine-readable JSON-LD that describes your content to engines.
Structured data (usually JSON-LD schema) is markup that tells engines what a page is, an Article, an FAQ, an Organization, a Product, and how its parts relate. It does not change what readers see, but it makes content far easier for machines to parse, classify and trust.
For AI visibility, valid FAQ and entity schema can help machines interpret and attribute content, but markup does not guarantee inclusion or citation. CiteTrack can generate supported FAQ and Article/Organization JSON-LD as reversible page improvements; related concept: entity.
Why — and when — does it matter?
Structured data clarifies entities and page properties for machines. It supports understanding but cannot compensate for missing, misleading or inaccessible visible content.
How it works
Select the Schema.org type that matches the page.
Map visible facts to valid properties.
Add stable entity identifiers and relationships.
Validate syntax and eligibility.
Keep markup synchronized with visible content.
Worked example
A product page marks price, availability, brand and reviews that users can also see. Adding invented ratings only in JSON-LD creates misleading markup and should not be done.
How to track and report it
Reporting rule: State the engine, prompt set, market, time window and denominator. A number without scope cannot be reproduced or compared.
Practical playbook
- Select the Schema.org type that matches the page.
- Map visible facts to valid properties.
- Add stable entity identifiers and relationships.
- Validate syntax and eligibility.
- Keep markup synchronized with visible content.
Common mistakes
- Marking up hidden facts
- Choosing a type only for a rich result
- Assuming schema guarantees AI citations
Questions people ask
What is Structured data (schema)?
Machine-readable JSON-LD that describes your content to engines. Structured data clarifies entities and page properties for machines. It supports understanding but cannot compensate for missing, misleading or inaccessible visible content.
How does Structured data (schema) work?
Select the Schema.org type that matches the page. Map visible facts to valid properties. Add stable entity identifiers and relationships. Validate syntax and eligibility. Keep markup synchronized with visible content.
How do you measure Structured data (schema)?
Valid eligible markup and entity consistency. Rich-result eligibility and parsing errors. Valid coverage = eligible pages with valid markup ÷ eligible pages × 100
What is a common mistake with Structured data (schema)?
Marking up hidden facts. The scope and methodology should be stated before interpreting the result.
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