Glossary

The terms behind AI search, answer engines and AI recommendations.

Each entry gives a quotable definition, why the term matters to a B2B SaaS team, a worked example and the misunderstandings we meet most often. RecoProof's own metrics link to their canonical definitions in the methodology.

Concepts

  • AI visibility

    AI visibility describes whether and how a brand appears in answers from AI assistants and AI search features: whether it is named, described accurately, cited and recommended for the questions its buyers ask.

  • Answer engine

    An answer engine is a system that responds to a question with a written answer, often generated by a language model from retrieved sources, instead of returning only a ranked list of links.

  • Answer engine optimization (AEO)

    Answer engine optimization (AEO) is the work of making a brand easy for AI answer engines to find, understand and cite, so it appears accurately in the answers buyers read instead of only in a list of links.

  • Brand mention vs recommendation

    A brand mention is an answer that names the brand; a recommendation is an answer that presents it as a plausible choice for the buyer's stated need. Every recommendation is a mention, but many mentions are not recommendations.

  • Buyer questions (prompt set)

    Buyer questions are the natural-language questions a prospective customer asks an AI assistant while researching a purchase. A prompt set is the fixed list of such questions a team measures repeatedly.

  • Citation (in AI answers)

    A citation in an AI answer is a visible link or reference to a source the engine used to support part of the answer, such as a numbered footnote, an inline link or a list of sources.

  • Entity (brand entity)

    An entity is a distinct, identifiable thing, such as a company, product or person, that search engines and language models treat as one concept however it is written. A brand entity is your company or product in that sense.

  • Generative engine optimization (GEO)

    Generative engine optimization (GEO) is the practice of improving how often and how accurately a brand's content is used in answers written by generative AI systems such as ChatGPT, Perplexity, Gemini or Google's AI Overviews.

  • Retrieval-augmented generation (RAG)

    Retrieval-augmented generation (RAG) is a technique in which a language model first retrieves relevant documents, such as web pages, and then writes its answer from them. Grounding is the related idea of tying an answer to such sources.

  • Zero-click search

    A zero-click search is a search that ends without the user clicking through to any website, because the results page or an AI answer already satisfied the question.

AI search products

  • AI Mode

    AI Mode is a conversational search experience in Google Search that answers a question with an AI-generated response, lets the searcher ask follow-up questions and links to pages across the web.

  • AI Overviews

    AI Overviews are AI-generated summaries that Google Search shows in its results for some queries, with links to supporting pages on the web.

  • ChatGPT search

    ChatGPT search is the capability that lets ChatGPT look up current information on the web and answer with inline citations linking to the pages it used.

  • Perplexity

    Perplexity is an AI answer engine that searches the web in real time and answers in conversational language, with numbered citations linking to its sources.

Crawlers and files

  • AI crawler

    An AI crawler is a bot that fetches web pages for an AI product: to collect training data, to build an index an assistant can cite, or to read a page live when a user asks. Most are managed in robots.txt by their user-agent token.

  • Google-Extended

    Google-Extended is a robots.txt token that lets publishers control whether content Google crawls from their site may be used to train future Gemini models and to ground answers in Gemini Apps and Vertex AI. It does not affect Google Search.

  • GPTBot

    GPTBot is OpenAI's web crawler for content that may be used to train its generative AI foundation models. Disallowing it in robots.txt indicates that a site's content should not be used for that training.

  • llms.txt

    llms.txt is a proposed Markdown file at the root of a website, /llms.txt, that gives AI tools a short, curated overview of the site: its name, a brief summary and links to the pages that matter most.

  • OAI-SearchBot

    OAI-SearchBot is OpenAI's crawler for surfacing websites in ChatGPT's search features. OpenAI says sites that opt out of it are not shown in ChatGPT search answers, though they can still appear as navigational links.

RecoProof metrics

  • AI Share of Voice

    RecoProof metric

    A brand's share of all mentions of it and its tracked competitors. AI Share of Voice divides the brand's mentions by its own mentions plus its tracked competitors' mentions in the measured answers.

  • Citation Share

    RecoProof metric

    How often a brand's own website is part of the evidence AI shows. Citation Share is the share of eligible answers that cite at least one page on the brand's own site.

  • Displacement Rate

    RecoProof metric

    How often a tracked competitor is recommended while the brand is not. Displacement Rate is the share of eligible answers in which the brand is not recommended and at least one predefined relevant competitor is.

  • Mention Rate

    RecoProof metric

    How often AI names a brand at all. Mention Rate is the share of eligible answers that name the brand, whether or not they recommend it.

  • Recommendation Gap

    RecoProof metric

    How often AI mentions a brand without recommending it. Recommendation Gap is the share of eligible answers that name the brand but do not recommend it, so it equals Mention Rate minus Shortlist Share.

  • Shortlist Share

    RecoProof metric

    How often AI puts a brand on the buyer's shortlist. Shortlist Share is the share of eligible answers to unbranded buyer questions that recommend the brand.