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AI Search and GEO: The Complete Glossary

AI search and GEO cover how AI assistants find a page, decide it is trustworthy, and quote it inside a written answer. That is a different job from ranking in a list of blue links, and it has its own vocabulary. The twenty terms below are the ones that come up most often when a business asks why ChatGPT names a competitor instead of them.

20 terms across 5 stages

  1. What GEO is

    The discipline itself, and the surface it competes for.

    Generative Engine Optimization (GEO)

    GEO is the practice of structuring your website so AI tools like ChatGPT, Perplexity, and Google AI Overviews cite or quote it directly inside their answers, instead of just linking to it.

    Traditional SEO competes for a spot in a list of blue links. GEO competes to be the source an AI assistant actually names when it writes a synthesized answer. The two share the same technical foundation — a crawlable, fast, trustworthy site — but GEO adds a layer on top: direct answers, original data, and clean structured data that make your content easy for a model to extract and confident to cite.

    See alsoAI CitationAnswer Engine Optimization (AEO)Retrieval-Augmented Generation (RAG)

    Answer Engine Optimization (AEO)

    AEO is writing and structuring content so it directly answers a specific question — often used interchangeably with GEO, though AEO leans more on Q&A formatting and featured-snippet-style answers.

    In practice, AEO means opening a section with the direct answer in the first sentence or two, phrasing headings as real questions, and using FAQ-style structure. It's one of the most reliable ways to earn both a Google featured snippet and an AI citation, since both surfaces are looking for the same thing: a clean, extractable answer.

    See alsoGenerative Engine Optimization (GEO)Featured SnippetPassage Ranking

    AI Overview

    An AI Overview is the AI-written summary Google shows above the normal search results, pulled from a handful of source pages and displayed before any of the traditional blue links.

    AI Overviews lean heavily on pages that already rank well in Google's organic results and carry clean schema markup — it's largely a reward layered on top of solid SEO, not a separate ranking system. A page that isn't in the top 10 organically for a query is unlikely to be pulled into the Overview for that same query either.

    See alsoGenerative Engine Optimization (GEO)Featured SnippetZero-Click Search

  2. What winning looks like

    The outcomes worth measuring once clicks stop telling the whole story.

    AI Citation

    An AI citation is when a tool like ChatGPT, Perplexity, or Google AI Overviews names your business or links to your page as the source behind part of its answer.

    Different platforms cite differently — Perplexity typically names far more sources per answer than ChatGPT, for example. Earning a citation generally comes down to three things: your page has to be found, the model has to be able to pull a clear answer out of it, and the model has to trust it enough to name you rather than paraphrase without credit.

    See alsoGenerative Engine Optimization (GEO)Brand MentionCitation Rate

    Citation Rate

    Citation rate is how often a page or domain gets named as a source across a set of AI-generated answers, usually tracked as a percentage over a batch of test questions.

    Tracking this over time — by asking the same panel of buyer questions on a recurring schedule — turns AI visibility from a one-time check into a measurable trend, the same way rank tracking works for traditional SEO.

    See alsoAI CitationShare of Voice (AI)AI Overview

    Brand Mention

    A brand mention is any instance where your business name appears in an AI-generated answer, article, or review — whether or not it comes with a clickable link.

    Unlinked mentions still matter: they build the entity association that helps AI tools connect your name to your category and reputation over time, even before a direct citation happens.

    See alsoAI CitationShare of Voice (AI)Entity (Search Entity)

    Share of Voice (AI)

    AI share of voice is the percentage of relevant AI-generated answers in which your brand gets mentioned, compared to your competitors.

    Measuring this means regularly asking AI tools the real questions your buyers ask — "who's the best X in [city]," "compare X vs Y" — and tracking whether you, a competitor, or nobody gets named. It's the AI-era equivalent of tracking keyword rankings.

    See alsoAI CitationCitation RateBrand Mention

  3. How the machines work

    The parts of an AI system that decide what it says about you.

    Large Language Model (LLM)

    A large language model is the type of AI system — like the ones behind ChatGPT, Gemini, and Claude — trained on huge amounts of text to understand and generate human language.

    LLMs power both the chat experience you type into directly and the "AI Mode" or "AI Overview" features layered into search engines. When an LLM is connected to live web search, it can look up current pages and cite them in its answer, which is the mechanism GEO is built around.

    See alsoGenerative Engine Optimization (GEO)Retrieval-Augmented Generation (RAG)Hallucination (AI)

    Retrieval-Augmented Generation (RAG)

    RAG is the process AI search tools use to find relevant web pages for a question, then feed those pages to the language model so it can write an answer with real sources attached.

    Instead of answering purely from what it learned in training, a RAG system converts your question into a search, pulls back a handful of matching passages from the web, and asks the model to summarize them with citations. This is why a page has to be crawlable and clearly written to be cited at all — if it's never retrieved, it can never be quoted.

    See alsoLarge Language Model (LLM)Passage RankingAI Crawler

    Training Data

    Training data is the large collection of text an AI model learned from before it was released — separate from the live web pages it might retrieve for a real-time answer.

    A model's baseline knowledge of your business comes from training data and can be outdated or simply wrong. Live-search-connected tools (like ChatGPT Search or Perplexity) correct for this by retrieving current pages at answer time — which is exactly the layer GEO work is aimed at influencing.

    See alsoLarge Language Model (LLM)Retrieval-Augmented Generation (RAG)Hallucination (AI)

    Hallucination (AI)

    A hallucination is when an AI tool confidently states something false or made up, rather than something it actually retrieved from a real source.

    Hallucinations happen more often when a model has too little reliable source material to draw from. Publishing clear, well-sourced, original information about your own business — instead of leaving gaps for the model to guess at — reduces the odds an AI tool answers a question about you incorrectly.

    See alsoLarge Language Model (LLM)Retrieval-Augmented Generation (RAG)AI Citation

    Prompt

    A prompt is the question or instruction a person types into an AI tool like ChatGPT — the modern equivalent of a search query.

    Understanding how your real customers phrase prompts (conversational, specific, often multi-part) rather than how they typed old-school keyword searches is central to writing content that actually gets surfaced in AI answers.

    See alsoConversational SearchAnswer Engine Optimization (AEO)Long-Tail Keyword

  4. How they reach your site

    Nothing below matters if these three go wrong.

    AI Crawler

    An AI crawler is an automated bot — like GPTBot, PerplexityBot, ClaudeBot, or OAI-SearchBot — that visits web pages to gather content either for AI model training or for live search retrieval.

    Blocking these bots in robots.txt removes your site from that platform's AI answers entirely, whether or not that was the intent. It's worth distinguishing training crawlers (which build future model knowledge) from search-retrieval crawlers (which power live, cited answers) before deciding what to block.

    See alsollms.txtRobots.txtRetrieval-Augmented Generation (RAG)

    llms.txt

    llms.txt is a proposed standard, plain-text file placed at the root of a website that gives AI models a clean, curated summary of the site's most important content.

    It works similarly to robots.txt or a sitemap, but instead of crawl rules or URLs, it offers a short, structured overview meant to help language models understand a site quickly. Adoption is still early and inconsistent across platforms, but it costs little to publish and signals a site is actively managing its AI presence.

    See alsoAI CrawlerRobots.txtXML Sitemap

    Passage Ranking

    Passage ranking is when a search or AI system evaluates and ranks individual sections of a page — not just the page as a whole — to find the single best-matching answer.

    This is why a single long article can rank or get cited for a very specific sub-question buried deep in the text. Writing each section as a self-contained, clearly headed answer improves its odds of being picked up by passage-level ranking, even if the rest of the page covers unrelated ground.

    See alsoSemantic SearchAnswer Engine Optimization (AEO)Featured Snippet

  5. How they understand meaning

    Why being a recognised thing beats matching a keyword.

    Entity (Search Entity)

    A search entity is a specific, uniquely identifiable thing — a business, person, place, or product — that search engines and AI tools track as a distinct concept rather than just a string of text.

    Search engines connect an entity to facts about it: your business entity is linked to your address, category, reviews, and website. The more consistent those facts are everywhere they appear, the more confidently an AI tool can recommend you by name instead of guessing which "Gobiya" or "Steve Martin" you actually are.

    See alsoKnowledge GraphNAP ConsistencyGoogle Business Profile (GBP)

    Knowledge Graph

    The Knowledge Graph is Google's internal database of entities and the verified facts connected to each one, used to power knowledge panels, map listings, and AI answers.

    Getting your business correctly represented in the Knowledge Graph — the right category, address, and description, consistent across your site and your Google Business Profile — makes Google (and by extension, Gemini) far more confident recommending you by name.

    See alsoEntity (Search Entity)Google Business Profile (GBP)NAP Consistency

Common questions

Is GEO different from SEO, or just a new name for it?

They share a foundation and diverge at the top. Both need a crawlable, fast, trustworthy site — a page that fails traditional SEO fails GEO too. What GEO adds is a layer aimed at extraction rather than ranking: direct answers in the opening sentence, original data, and clean structured markup that make a passage easy to lift and safe to attribute.

Do I need to do GEO separately for each AI platform?

Largely yes. In our analysis of 3,217 citations across ChatGPT, Gemini, Perplexity, Claude, and Copilot, only 2.7% of cited domains were cited by all five. Overlap between platforms is low enough that visibility on one should not be assumed to transfer to another.

What single change most improves the odds of being cited?

Publishing original data. In the same analysis, pages containing first-party statistics or original research were cited 4.5x more often than pages without — the strongest single signal we measured, and a far larger effect than domain authority, which showed only a 15% premium.

Does llms.txt actually do anything yet?

Adoption is not universal and it is not a requirement for being cited. It is cheap to add and does no harm, but it belongs well below crawlability, page speed, and answer-first writing on any realistic priority list.

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