AI Visibility and GEO glossary
Short, precise definitions of the terms that come up whenever the subject is getting cited by AI. Each entry has its own page, marked up with DefinedTerm schema. For a longer treatment of these concepts, see the Learn hub.
AI Visibility
A brand's ability to be found, understood and cited by AI assistants when someone asks a question about its market.
GEO (Generative Engine Optimization)
The practice of optimizing content to be cited in the answers produced by generative AI engines such as ChatGPT, Perplexity and Gemini.
AI crawler
The bot that collects content from the web to feed AI assistants: GPTBot, ClaudeBot, PerplexityBot and others. None of them run JavaScript.
Structured data (JSON-LD / Schema.org)
Markup that describes a page's content to machines: what it is, who wrote it and when it was published.
E-E-A-T
Experience, Expertise, Authoritativeness and Trustworthiness: the credibility signals that search engines and AI systems use to pick sources.
Target prompt
The natural-language question a brand wants to be cited in by an AI. It is the unit of measurement for AI Visibility.
Anchor answer
The sub-45-word paragraph under a question-form heading, written to be retrieved on its own and cited by an AI.
Citation rate
The percentage of target questions in which the brand is cited in AI answers, the central metric of AI Visibility.
llms.txt
The Markdown file at the root of a website that gives AI systems a curated map of the main pages, with summaries.
AEO (Answer Engine Optimization)
Optimizing content for answer engines: being the source cited inside the answer, not a position in a list of links.
LLMO (Large Language Model Optimization)
Optimizing so the model finds, understands and repeats correctly what a brand states about itself.
AISO (AI Search Optimization)
Optimizing for AI-mediated search surfaces, from assistants to answers generated inside search engines.
Query fan-out
The technique where an engine breaks a question into several simultaneous sub-searches and merges the results into one answer.
Latent intent
The question the user never typed, which the engine infers and searches anyway. Where citation competition is thinnest.
Relevance engineering
The term iPullRank uses for the discipline that succeeds SEO: engineering relevance for any search surface.
AI share of voice
The slice of citations a brand holds against every competitor cited in the same answers.
Citation gap
The target questions where the brand is absent and a competitor is cited. The most actionable work list there is.
Retrieval
The step where the system finds and selects the sources behind a generated answer. What is not retrieved cannot be cited.
AI Visibility baseline
The frozen record of how AI answers about a brand before anything is published. Without it, nothing is demonstrable later.
AI Overviews
Google’s AI-generated summary at the top of search. Access is governed by Googlebot, not Google-Extended.
AI Mode
Google’s conversational search experience for complex questions, powered by query fan-out.
ReBo method
The AI Visibility methodology of six delivery workstreams, with progress measured across four levels.
Frequently asked questions about this glossary
What is the difference between AI Visibility and GEO?
AI Visibility is the outcome: being found, understood and cited by AI systems. It is what you measure. GEO, or Generative Engine Optimization, is the discipline that produces that outcome, and it is what you practice. You do GEO to build AI Visibility.
Do I need a technical background to apply these concepts?
Not to make the decisions. These terms exist precisely so that portfolio managers, investor relations and marketing can talk to IT without a middleman. The technical work (static HTML, structured data and clearance for the crawlers) is specific and finite, and any technology team can deliver it once the request is clear.
Where should I start if I can only read three entries?
Start with AI Visibility, the umbrella concept; then AI crawler, which explains who is actually reading your website; and then citation rate, the metric that measures all of it.
Are these industry-standard terms or ReBo coinages?
AI Visibility, GEO, E-E-A-T, AI crawler, structured data and llms.txt are industry terms, and each entry states where they came from. What belongs to ReBo is the 4-level framework and the way it organizes the five citation factors, always labeled as such.
Where can I see these concepts applied in practice?
In the Learn hub, which brings together three pillar articles and four satellite pieces covering the factors, the data and the cases. For how the work runs, see the ReBo method; for the delivery itself, see the service.