GEO & AI Search Glossary

The strategic practice of optimizing web content, entity data, and technical structure so your brand is cited and recommended as a top answer by Large Language Models (ChatGPT, Claude, Gemini).

A core subset of SEO focused on structuring content into clear, direct answers so AI assistants and conversational models can easily parse and synthesize it.

The percentage of AI search responses within a specific niche or prompt set that explicitly cite your domain versus your direct competitors.

An AI model framework that combines real-time search index retrieval with LLM generation to deliver factual, up-to-date answers grounded in web source citations.

The configuration of robots.txt directives and HTTP headers to allow or block dedicated AI web crawlers (such as OAI-SearchBot, ClaudeBot, and Googlebot-Extended).

A structured network of interconnected nodes representing real-world people, organizations, concepts, and products that LLMs use to verify factual accuracy and authority.

A machine-readable linked data format embedded in HTML that explicitly defines brand attributes, author credentials, product pricing, and organizational relationships for AI engines.

The proportion of unique, factual, and actionable data relative to total word count. High information density is heavily favored by LLMs when summarizing web pages.

A user query resolved entirely within an AI-generated answer or AI Overview, where the user receives their answer without needing to click out to traditional organic links.

A standardized benchmark score measuring how consistently a brand is recommended across high-intent transactional prompts in AI search engines.

Using meaningful HTML tags (like <article>, <section>, <table>, <header>) to give AI parsers clear structural context about web page content.

The practice of publishing unambiguous, structured, and consistent factual data across owned channels to prevent AI models from generating false claims about a brand.