// Glossary · content

Schema Markup

Also: structured data · JSON-LD

Machine-readable metadata that tells search engines what a page is (Article, Service, FAQ, Product). Powers rich results and AI Overview citations.

Schema markup is structured data embedded in a page (almost always as JSON-LD in a script tag) that tells search engines what the page is and what entities it contains. Common types include Article, BlogPosting, Service, Product, Organization, FAQPage, DefinedTerm, BreadcrumbList, and HowTo. The vocabulary comes from schema.org, a joint Google, Microsoft, Yahoo, and Yandex project that standardized how machines read web pages. A page without schema is readable; a page with schema is parseable, which is the difference between a search engine guessing the page topic and knowing it.

The practical effect of schema is twofold. First, it powers rich results: review stars, FAQ accordions in search, breadcrumb trails, product price snippets, video thumbnails. These visual treatments lift click-through by 15 to 35% on the queries where they appear. Second, it lifts eligibility for AI Overview citations. Synthesizers preferentially pull from pages with explicit DefinedTerm or FAQPage markup because the markup tells the model where the answer lives. A glossary page with proper DefinedTerm schema is far more likely to be cited than a similar page without it.

For funded teams running programmatic SEO at scale, schema is non-negotiable infrastructure. Every page in a programmatic cluster should carry the schema type that matches its purpose: Service for service pages, Product for product pages, Article for blog posts, FAQPage for any page with a FAQ section. The AI Content Department ships pages with the appropriate schema baked into the template rather than retrofitting it later. Retrofitting schema across 400 pages is the kind of unpaid maintenance work that quietly tanks programmatic SEO projects.

// Examples
  • A glossary page adds DefinedTerm + FAQPage schema and captures the AI Overview citation slot within 14 days of indexation.
  • A service page adds Service + AggregateRating schema and lifts click-through on the target query from 3.1% to 4.7%.
  • A product comparison page adds Product + BreadcrumbList schema and starts rendering rich results that the competitor pages do not.
// Common questions
Does schema markup directly improve rankings?
Not as a direct ranking factor in the way page speed or backlinks are. It improves eligibility for rich results and AI Overview citations, both of which improve effective traffic at any given ranking position. A page at position 4 with rich results often outperforms a page at position 2 without them.
What is the difference between JSON-LD and microdata?
Both are valid syntaxes for schema markup. JSON-LD is a script block embedded in the page head or body. Microdata sprinkles attributes through the HTML. Google strongly prefers JSON-LD because it is cleaner to parse and easier to maintain. New schema implementations should use JSON-LD exclusively.
How do I know if my schema is working?
Run the page through the Google Rich Results Test. It reports which schema types are detected, which are valid, and which would be eligible for rich result rendering. Google Search Console also reports schema errors at the property level under the Enhancements tab.
Should every page have schema markup?
Every public-facing page that targets search traffic, yes. The schema type depends on the page purpose: Article for blog content, Service for service pages, Product for product pages, FAQPage for any page with a meaningful FAQ. Admin pages, login flows, and other non-indexed pages do not need schema.
// Related terms
// Ready to ship?

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