Schema Markup
Structured data code that helps search engines and AI systems understand the context and meaning of your content.
Full Definition
Schema Markup (also called structured data) is a standardized vocabulary of tags that you add to your HTML to help search engines and AI systems understand the context, meaning, and relationships within your content. It uses the Schema.org vocabulary and is typically implemented as JSON-LD.
Why Schema Matters for AI:
- Provides explicit context about content type and purpose
- Enables rich snippets and enhanced search results
- Helps AI systems extract accurate information
- Improves content trustworthiness signals
Key Schema Types for GEO:
Organization
Identifies your company, logo, social profiles, and contact information.
Article/BlogPosting
Marks up content with author, date, headline, and description.
FAQPage
Structures Q&A content for easy AI extraction.
HowTo
Outlines step-by-step instructions.
Product/SoftwareApplication
Describes products with features, pricing, and reviews.
Person
Identifies authors and their credentials.
BreadcrumbList
Shows site navigation hierarchy.
Implementation Example:
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [{
"@type": "Question",
"name": "What is GEO?",
"acceptedAnswer": {
"@type": "Answer",
"text": "GEO stands for..."
}
}]
}
Proper schema implementation is a fundamental GEO best practice that helps AI systems accurately understand and cite your content.
Keywords
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