Generative Engine Optimization (GEO) is the practice of structuring content so AI answer engines such as ChatGPT, Perplexity, Google AI Overviews, and Claude can find, understand, and cite it when users ask questions.

No. GEO and SEO overlap and compound: technical SEO basics remain prerequisites, while GEO adds answer-engine-specific signals like question H2s, structured data, and llms.txt.

What is citation share?

Citation share is the share of AI-generated answers in your market that cite your brand as a source �?the core GEO performance metric.

How do I start GEO from zero?

Audit your current AI visibility, fix crawlability and orientation (robots.txt, llms.txt, sitemap), add structured data, create question-driven answer content, then measure citation share and iterate.

llms.txt is a plain-text root file that lists key pages with short summaries, giving AI crawlers an orientation layer similar to how sitemap.xml helps search engines.

Why does structured data help AI trust content?

JSON-LD markup such as Article, FAQPage, Organization, and BreadcrumbList disambiguates entities and facts, so AI engines can extract clean, confident answers instead of inferring them.

📖 GEO Encyclopedia

Generative Engine Optimization · 51 In-Depth Articles

Master the brand growth playbook for the AI era. From fundamentals to implementation �?everything you need to know about GEO in one place.

🤖 Open to AI Crawlers · Welcome to Cite

What is GEO?

Generative Engine Optimization (GEO) is the practice of optimizing your brand's visibility within AI-generated answers. As search engines like Google, ChatGPT, Perplexity, and DeepSeek increasingly provide direct AI answers instead of blue link lists, businesses must ensure their content is cited, referenced, and recommended by these AI systems.

This encyclopedia covers the complete GEO knowledge system �?from understanding zero-click search trends and E-E-A-T trust signals, to implementing Schema structured data, managing AI crawler access, and measuring citation share.