AI search glossary

The terms behind Generative Engine Optimization and AI visibility, each defined in two sentences, then explained with an example.

• AI visibility score

  An AI visibility score is the percentage of AI-generated answers, across a defined set of buyer prompts and AI engines, that mention your brand.

• Answer engine

  An answer engine is a search system that responds to a question with a direct, written answer, usually generated by AI and often with cited sources, instead of a ranked list of links.

• Answer Engine Optimization (AEO)

  Answer Engine Optimization (AEO) is the practice of structuring content so that answer engines can quote it directly as the answer to a question.

• Brand mentions

  Brand mentions are references to a brand by name on pages it does not own, such as reviews, articles, forums and directories, whether or not they link to it.

• ChatGPT search

  ChatGPT search is the capability that lets ChatGPT retrieve current information from the web and cite its sources inside an answer.

• Citations in AI answers

  Citations in AI answers are the links an AI engine shows to the web pages it used to build its answer.

• E-E-A-T

  E-E-A-T stands for Experience, Expertise, Authoritativeness and Trustworthiness, the qualities Google's Search Quality Rater Guidelines ask human raters to look for when judging content.

• Entity SEO

  Entity SEO is the practice of helping search engines and AI models recognize a brand, person or product as a distinct entity with consistent, well-defined attributes.

• Generative Engine Optimization (GEO)

  Generative Engine Optimization (GEO) is the practice of making a brand easy for generative AI engines such as ChatGPT, Perplexity and Gemini to find, trust and recommend.

• Google AI Overviews

  Google AI Overviews are AI-generated summaries that appear above the regular results for some Google searches, with links to the web pages used to build them.

• Grounding

  Grounding is the process of tying an AI model's answer to external sources retrieved at answer time, such as live web search results, rather than relying only on what the model memorized in training.

• Knowledge cutoff

  A knowledge cutoff is the point in time after which a language model has no information from its training data.

• LLM SEO

  LLM SEO is the work of improving how large language models (LLMs) describe and recommend a brand, both from what they learned in training and from pages they retrieve at answer time.

• llms.txt

  llms.txt is a proposed web standard for a plain Markdown file, served at /llms.txt, that gives large language models a short, curated summary of a website and links to its most useful pages.

• Perplexity SEO

  Perplexity SEO is the practice of getting a brand mentioned and its pages cited in answers from Perplexity, an AI answer engine that searches the web for nearly every question.

• Prompt tracking

  Prompt tracking is the practice of asking AI engines the same set of buyer questions on a regular schedule and recording which brands each answer names, in what order, and which sources it cites.

• Retrieval-augmented generation (RAG)

  Retrieval-augmented generation (RAG) is a technique in which an AI system first retrieves documents relevant to a question, then passes them to a language model to write the answer.

• Schema markup for AI

  Schema markup is structured data, usually written as JSON-LD using the schema.org vocabulary, that describes the facts on a page, such as an organization, product, price, review or FAQ, in a machine-readable format.

• Share of voice in AI

  Share of voice in AI is the proportion of brand mentions in AI-generated answers that go to your brand, compared with competitors, across the same set of buyer prompts.

• Zero-click search

  A zero-click search is a search where the user's question is answered on the results page itself, through a snippet, an AI Overview or an AI chat answer, so they never click through to a website.