What Is Schema Markup? Definition
Structured data in JSON-LD format that helps search engines understand a page's content.
What is schema markup?
Schema markup (also called structured data) is a standardized vocabulary from schema.org that makes web content machine-readable for search engines and AI systems. It is usually implemented in JSON-LD format.
Example: a page answers common customer questions. A JSON-LD block of the type FAQPage in the page's code lists each question and its answer, so search engines and AI systems can read them as clearly marked question-and-answer pairs.
Benefits of schema markup
- Rich snippets – enhanced display in search results (stars, prices, FAQs)
- AI understanding – helps ChatGPT and similar systems interpret your content correctly
- Knowledge Graph – increases the chance of being included in Google's knowledge base
- Voice search – voice assistants use structured data for their answers
Schema markup and GEO
For AI visibility, schema markup is one of the most important levers. AI systems prefer machine-readable content. Types such as Article, FAQPage, HowTo, Organization and Product help your content get cited as a source in AI answers.
This page gives a short definition. For a step-by-step implementation, read our schema markup guide. If you want it done for you, see our technical SEO service.
Frequently asked questions
What is schema markup?
Schema markup, also called structured data, is a standardized vocabulary from schema.org that makes web content machine-readable. It is usually implemented in JSON-LD format.
Why does schema markup matter for SEO?
It enables rich snippets in search results and helps AI systems interpret your content correctly. For AI visibility, it is one of the most important levers.
What is an example of schema markup?
A page with customer questions adds a JSON-LD block of the type FAQPage that lists each question and answer. Other common types are Article, HowTo, Organization and Product.