Glossary
GEO & AI visibility glossary
Plain-language definitions of the terms behind getting cited by AI search — from GEO and AEO to entities, RAG, and structured data.
- Generative Engine Optimization (GEO)
- The practice of getting a brand cited, quoted, and recommended inside AI-generated answers from tools like ChatGPT, Perplexity, Google AI Overviews, Claude, and Gemini, rather than ranking for a link on a results page.
- Answer Engine Optimization (AEO)
- Optimizing content so it is selected and cited as the answer by AI answer engines. AEO is used interchangeably with GEO; it emphasizes the "answer engine" that returns a direct response.
- AI Visibility
- How often and how prominently a brand is named, cited, or recommended when people ask AI tools questions in its category. It barely correlates with Google rankings and is measured as its own channel.
- Citation
- In AI search, the unit of visibility: whether an answer engine names a brand, quotes its content, or links it as a source when composing a response.
- Citation Audit
- A structured review of where AI tools currently pull answers for a business’s buyer-intent queries, showing where the brand is present, absent, or misrepresented, and which sources it needs to appear in.
- Entity
- A distinct thing a search or AI system recognizes — a company, person, product, or concept — with consistent attributes. Being a well-modeled entity helps AI systems describe and recommend a brand accurately.
- Entity SEO
- Optimizing so search and AI systems recognize a brand as a distinct, consistent entity — through structured data, matching facts across the web, and authoritative references — rather than just a set of keywords.
- Knowledge Graph
- Google’s database of entities and the relationships between them. A strong Knowledge Graph presence helps Google and Gemini understand and confidently surface a brand.
- Large Language Model (LLM)
- An AI model trained on large amounts of text that generates natural-language responses. LLMs like GPT, Claude, and Gemini power the answer engines GEO targets.
- Retrieval-Augmented Generation (RAG)
- A technique where an AI model retrieves relevant documents at query time and grounds its answer in them. RAG is why retrievable, extractable content and trusted sources influence AI citations.
- Structured Data
- Machine-readable markup (schema.org, usually JSON-LD) that describes a page’s content and entities, helping search engines and AI systems parse and attribute it. Most AI crawlers only see it in static HTML.
- AI Overviews
- Google’s AI-generated answer summaries shown above traditional results, drawn from Google’s index and citing a handful of sources.
- llms.txt
- A plain-text file at a site’s root that summarizes what the site and company do for LLM ingestion, helping AI systems understand and represent the brand.
- Answer-first content
- Writing that states the direct answer in the first one or two sentences, one question per page — the format AI engines most readily extract and quote.
- Share of Voice
- In AI visibility, how often a brand is named versus its competitors across a set of test queries — a core metric for tracking GEO progress.
New to the topic? Start with what GEO is and answer engine optimization, then score your GEO readiness.
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