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Glossary

The AI search ranking glossary.

Clear, non-hyped definitions of the terms that shape how ChatGPT, Perplexity, and Google AI decide which firms to name and cite.

AI Overviews

AI Overviews is Google's AI-generated answer box that appears above traditional results and summarizes an answer with links to supporting sources.

AI search ranking

Also: AI visibility

AI search ranking is getting a business named, recommended, or cited in the answers AI assistants like ChatGPT, Perplexity, and Google AI Overviews give to buyer questions.

Answer engine optimization

Also: AEO

Answer engine optimization (AEO) is the practice of structuring content and signals so answer engines can extract, trust, and surface a direct answer to a user's question.

Answer-first content

Answer-first content is writing that states the direct answer to a question in the first one or two sentences, so engines and readers can extract it immediately.

Citation share

Citation share is the proportion of the source links an AI engine cites in its answers that point to a given site, across a tracked set of queries.

Entity optimization

Also: Entity SEO

Entity optimization is the work of making a business a clearly defined, consistently described entity that search and AI systems can recognize, disambiguate, and trust.

Generative engine optimization

Also: GEO

Generative engine optimization (GEO) is the practice of optimizing a brand and its content to be cited and recommended by generative AI answer engines.

Grounding

Grounding is when a language model bases its answer on retrieved external sources and citations rather than on its own trained-in memory.

llms.txt

llms.txt is a proposed plain-text file at a site's root that offers AI models a curated, readable guide to the site's most important content.

Query fan-out

Query fan-out is when an AI engine expands a single user question into several related searches, then synthesizes one answer from the results it retrieves.

Retrieval-augmented generation

Also: RAG

Retrieval-augmented generation (RAG) is an architecture where a model retrieves relevant documents at query time and uses them to generate a grounded, citable answer.

Share of answers

Share of answers is the percentage of a tracked set of buyer queries where an AI engine names a given firm, measured consistently over time.

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