AI search, defined.

Answer Engine Optimization (AEO) is the practice of structuring content so that a search or AI system selects it as the direct answer to a question, rather than as one link among many. It focuses on concise, self-contained answers, explicit question-and-answer formatting, and structured data.

Generative Engine Optimization (GEO) is the practice of increasing the likelihood that a large language model cites a given source when generating an answer. It depends heavily on third-party mentions the model retrieves, not only on the brand's own website.

llms.txt is a proposed plain-text file placed at the root of a domain that summarises the site and lists its most important pages for large language models. It is a voluntary convention, not a standard, and no engine is obliged to read it.

AI Overviews are AI-generated summaries that appear above traditional results on Google, synthesising information from multiple web sources with links to those sources. They were previously tested under the name Search Generative Experience (SGE).

AI crawlers are automated agents operated by AI companies that fetch web content either to build training corpora or to retrieve sources at the moment a user asks a question. The two purposes use different user agents and are controlled separately in robots.txt.

A zero-click search is a search that ends without the user visiting any external website, because the result page itself satisfied the query through a featured snippet, knowledge panel, or AI-generated summary.

Citation share is the proportion of tracked questions in which a given brand or domain is cited as a source by an AI engine, relative to the total number of questions tracked or to competitors cited on the same questions.

Structured data is machine-readable markup, usually JSON-LD following the schema.org vocabulary, that states explicitly what a page is about — its type, author, price, questions and answers — instead of leaving those facts to be inferred from prose.