Part of AI Search Optimization
Generative Engine Optimization (GEO)
GEO is the practice of optimizing a website so generative AI engines (ChatGPT, Claude, Gemini, Perplexity, Copilot) cite it when answering user questions.
Overview
Generative Engine Optimization extends classical SEO into the answer layer of the web. Where SEO targets the ranked link, GEO targets the cited sentence inside an AI-generated response. The discipline combines crawl access (robots.txt, llms.txt), structured data (JSON-LD, FAQPage, Organization), entity clarity (consistent naming, sameAs links), and answer-shaped content (concise definitions, lists, Q&A blocks).
Components
- llms.txt
Plain-text index for LLM crawlers
- AI-aware robots.txt
Permission layer for AI bots
- JSON-LD structured data
Machine-readable entity markup
- FAQ schema
Extractable Q&A pairs
- ai-plugin.json
Manifest for agent discovery
Related entities
- AEO (Answer Engine Optimization) — sibling discipline
- SEO — parent discipline
- ChatGPT — target engine
- Perplexity — target engine
Key facts
- GEO sites that publish llms.txt see 3–7× higher AI citation rates within 60 days.
- FAQPage and HowTo schema are the highest-leverage structured data for AI extraction.
- GEO complements rather than replaces classical SEO — both run together.