AI crawler
A bot that fetches web content for AI systems — e.g. GPTBot, ClaudeBot, PerplexityBot, Google-Extended. Allowing the right crawlers is a prerequisite for being cited.
AEO & GEO Glossary
Plain-English definitions of the terms behind AI search, answer engines, and brand visibility.
AI Mode
Google’s fully conversational, generative search experience that answers follow-up questions in a chat-like flow, using query fan-out to pull from many sources.
AI OverviewsAIO
Google’s AI-generated summary shown above traditional results. It cites a handful of sources, making inclusion a primary AEO goal for Google traffic.
AI Share of Voice
The share of AI answers about a topic in which your brand is mentioned or cited, relative to competitors. The headline metric for AEO performance.
Answer Engine
A system that returns a single synthesized answer to a query instead of a ranked list of links. Examples include ChatGPT, Perplexity, Claude, and Google’s AI Mode.
Answer Engine OptimizationAEO
The practice of optimizing a brand’s content and entities so they are surfaced, cited, and recommended inside AI-generated answers rather than a list of links. AEO targets answer engines like ChatGPT, Perplexity, and Google AI Overviews.
Citation
A linked or named source an AI answer attributes information to. Earning citations — not just mentions — is the core objective of AEO.
E-E-A-T
Experience, Expertise, Authoritativeness, and Trust — quality signals search and answer engines use to judge whether a source is worth surfacing. Strong E-E-A-T improves the odds of being cited.
Embeddings
Numeric vector representations of text that capture meaning, letting systems match content to a query by semantic similarity rather than exact keywords.
Entity
A distinct thing an AI or search system can recognize and reason about — a brand, product, person, or place. Strong, consistent entity signals help models associate your brand with the right topics.
Generative Engine OptimizationGEO
Optimizing content to be retrieved and synthesized by generative AI systems. GEO overlaps heavily with AEO; the term emphasizes influencing what a generative model composes, not just which sources it links.
Grounding
Tying a model’s answer to verifiable external sources. Grounded answers cite those sources — which is exactly the citation AEO aims to win.
Hallucination
When an AI states something false or unsupported with confidence. Well-grounded, citable content reduces hallucinations about your brand.
Knowledge graph
A network of entities and their relationships that engines use to reason about the world. Being represented accurately in the knowledge graph strengthens brand associations in AI answers.
Large Language Model OptimizationLLMO
An umbrella term for making a brand visible and accurately represented across large language models — spanning training data, retrieval, and answer synthesis.
llms.txt
A proposed root-level file that gives AI systems a curated, machine-friendly map of a site’s most important content — an AEO analog to robots.txt and sitemap.xml.
Mention rate
How often your brand appears across a tracked set of prompts and engines. A primary indicator of AI visibility over time.
Perplexity
An answer engine that composes cited responses in real time from web retrieval. Its visible citations make it a common benchmark for measuring AEO performance.
Prompt
The natural-language input a user gives an AI engine. In AEO, the set of prompts a brand wants to appear in is the equivalent of a keyword list in classic SEO.
Query fan-out
A technique where an engine expands one user query into many sub-queries, retrieves for each, and synthesizes the results — widening the pool of sources that can be cited.
Retrieval
The step where an AI system selects candidate documents to inform an answer, typically via semantic (vector) similarity to the query.
Retrieval-Augmented GenerationRAG
An architecture where a model retrieves relevant documents at query time and grounds its answer in them. RAG is why fresh, well-structured, crawlable content can be cited even if it wasn’t in the training data.
Sentiment
Whether an AI answer frames your brand positively, neutrally, or negatively. AEO cares not only about being mentioned, but about how you are described.
Structured data
Machine-readable markup (Schema.org / JSON-LD) that describes a page’s entities and relationships, helping engines understand and confidently cite the content.
Vector search
Finding the most semantically similar content to a query by comparing embeddings. It underpins how RAG systems retrieve sources to cite.
Zero-click search
A query that is answered directly on the results surface, so the user never clicks through to a website. AI answers dramatically increase zero-click behavior, shifting value from traffic to citation.