Schema Markup
A specific vocabulary of tags added to HTML that creates an enhanced description of web content for search engines and AI systems.
Schema Markup is a semantic vocabulary defined by Schema.org that webmasters add to their HTML to improve how search engines and AI systems read and represent their content. It uses a standardized set of types and properties to describe entities like organizations, products, events, articles, reviews, and more.
For AI visibility, Schema Markup is essential because it provides explicit signals that help language models understand the factual context of content. For example, Organization schema tells AI systems a company's name, description, founding date, and official URLs—reducing the chance of misattribution or hallucination.
Best practices include implementing JSON-LD format, covering all relevant schema types for your business, keeping markup accurate and up-to-date, and validating with Google's Rich Results Test or Schema.org validators.
Related Terms
Structured Data
Standardized code formats (like Schema.org markup) that help search engines and AI models understand the content and context of web pages.
Knowledge Graph
A structured database of entities and their relationships used by search engines and AI models to understand real-world concepts.
LLM Optimization
The practice of adapting content and digital presence to be better understood, indexed, and referenced by large language models.
AEO Vision Content Team
Insights on AI search visibility, answer engine optimization, and brand discovery across ChatGPT, Perplexity, Gemini, Claude, and Google AI Mode.
Track your Schema Markup performance
AEO Vision helps brands measure and improve their AI search visibility across every major platform.