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AEO Glossary

Plain-language definitions for the terms that come up most when talking about answer engine optimization.

AEO (Answer Engine Optimization)

The practice of making a business citable by AI assistants (ChatGPT, Claude, Perplexity, Google AI Overviews) when buyers ask category questions. Rewards structured data, third-party corroboration, and consistent entity information rather than backlinks alone.

Answer Engine

A search or assistant interface (ChatGPT, Perplexity, Claude, Google AI Overviews) that returns a synthesized answer to a query instead of a ranked list of links.

Citation

An instance where an AI engine references or names a specific business, page, or source when answering a query. The core unit of visibility measured in AEO.

Share of Voice

The percentage of a defined set of buyer-relevant prompts in which a given brand is cited by an AI engine, relative to competitors.

Schema Markup (JSON-LD)

Structured data embedded in a page’s HTML that explicitly labels entities, relationships, and facts (e.g. FAQPage, Organization, Product) so crawlers and LLMs can parse them reliably.

llms.txt

A plain-text file at a site’s root, similar to robots.txt, that lists canonical pages for AI assistants to reference, grouped by category.

Knowledge Graph

A structured, cross-referenced set of facts about an entity (a business, person, or product) that AI systems draw on to answer questions. Can be owned (published on a company’s own domain) or third-party (Wikipedia, Wikidata).

Entity Consistency

The degree to which a business’s name, description, and facts match across its website, social profiles, and third-party listings. Inconsistency weakens AI engines’ confidence in citing a source.

AI Overview

Google’s AI-generated summary shown above traditional search results for many queries, synthesized from multiple sources rather than linking to a single page.

Crawlability

Whether a page’s content is actually readable by automated crawlers (including AI bots like GPTBot and ClaudeBot) at the HTML level, as opposed to being rendered only client-side via JavaScript.

E-E-A-T

Experience, Expertise, Authoritativeness, Trustworthiness: a framework increasingly used as a heuristic for how much weight AI engines give a source.

RAG (Retrieval-Augmented Generation)

A technique where an AI model retrieves relevant documents from an external source before generating an answer, rather than relying solely on its training data. Much of real-time AI search visibility depends on being retrievable this way.