Generative Engine Optimization (GEO)
Generative Engine Optimization (GEO) is the practice of structuring and writing content so that AI systems — like ChatGPT, Claude, Gemini, and AI search — can retrieve it, understand it, trust it, and cite it in their answers.
How it works
As people increasingly ask AI assistants instead of searching links, being mentioned in those AI answers becomes as important as ranking on a search page. GEO focuses on the qualities that make content citable: clear structure, self-contained answers, factual accuracy, and trust signals.
It overlaps with SEO — good technical foundations and authority still matter — but adds an emphasis on meaning-based retrieval and being genuinely useful and quotable, since AI systems pull passages, not just whole pages.
A closely related term is Answer Engine Optimization (AEO), which emphasizes directly answering the specific questions people ask.
How SiteMind uses it
GEO is why this glossary and SiteMind’s other resources exist: clear, self-contained, accurate content helps AI systems understand and recommend the product — and the same principles help your SiteMind assistant give clean, quotable answers to your visitors.
Related terms
Source grounding
Source grounding means every answer an AI gives is tied to and backed by specific retrieved content, and can be traced back to it.
Semantic search
Semantic search finds content by meaning rather than exact keywords, so it can match a question to the right answer even when the words differ.
Retrieval-Augmented Generation (RAG)
Retrieval-Augmented Generation (RAG) is a method where an AI looks up relevant information from a trusted source before answering, so its replies are grounded in facts instead of guesses.
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