What is Schema Markup?
Definition & Overview
Maintained by Schema.org, schema markup translates unstructured human web copy into explicit, machine-readable key-value pairs representing FAQs, products, organizations, and articles.
Analogy & Mental Model
Schema markup is like attaching a nutrition facts label to a food item so consumers and inspectors know exact ingredients instantly.
Why Schema Markup Matters
Schema markup provides structured ground truth data that RAG scrapers and Google AI Overviews extract directly to populate search features and citations.
Concrete Real-World Application
Embedding JSON-LD FAQPage markup on a pricing page so Google displays expandable Q&A accordions directly in search results.
How Schema Markup Works
Injected into page HTML headers as JSON-LD script blocks.
Core Components & Mechanisms
Entity Definition
Declaring the primary `@type` (e.g., Organization, DefinedTerm, Article).
Attribute Value Assignment
Mapping specific properties like `name`, `description`, `url`, `sameAs`, and `author`.
Machine Validation
Testing markup using Schema Validator and Google Rich Results Test tools.
Schema Markup vs Entity SEO
Entity SEO is the concept of defining real-world entities, whereas Schema Markup (JSON-LD) is the code syntax used to declare those entities to search engines and AI scrapers.
Frequently Asked Questions
Which schema types are most important for AEO?
Organization, Product, DefinedTerm, FAQPage, Article, and Person schemas carry the highest weight for AI search parsing.
Articles & Research Referencing Schema Markup
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