AEO & GEO Terms
AI search moves fast and comes with its own vocabulary. This glossary breaks down the AEO and GEO terms you need to know to understand how ChatGPT, Gemini, Perplexity, and Google AI Overviews decide what to cite.
AEO and GEO glossary, A to Z
20 terms from AI search, each defined in one sentence. Last reviewed 19 August 2026.
AI Overview
Google’s AI-generated summary shown above traditional results, synthesizing information from multiple sources into one direct answer, often with source links beneath it.
Answer Engine Optimization (AEO)
Structuring content in clear, self-contained question-and-answer formats so voice assistants and answer boxes can lift a direct response from your page.
Chat Referral Traffic
Visits arriving at your site from links shared inside AI chat interfaces like ChatGPT or Perplexity, a newer analytics category alongside organic and paid traffic.
Citation (AI Citation)
An instance where an AI system names or links to your brand or page as the source behind a generated answer.
Context Window
The amount of text an AI model can consider at once when generating a response. Longer context windows let models read more of a page before summarizing it.
Conversational Query
A search phrased as natural spoken language rather than short keywords, common in voice search and AI chat, e.g. what’s the best CRM for a 10 person team instead of best CRM small business.
Embeddings
Numerical representations of text that let AI systems measure how semantically similar two pieces of content are, used heavily in retrieval and ranking within AI search tools.
Entity
A specific, well-defined thing (a person, brand, place, or concept) that search engines and AI models recognize and connect across the web, rather than just matching text strings.
Generative Engine Optimization (GEO)
The practice of optimizing content specifically to be retrieved, summarized, and cited by generative AI tools such as ChatGPT, Gemini, and Perplexity.
Hallucination
When an AI model generates information that sounds plausible but is factually incorrect or unsupported by any real source, a key risk brands must monitor around AI-generated mentions.
Knowledge Graph
A structured database of entities and their relationships that search engines use to understand facts about the world, powering knowledge panels and some AI answers.
Large Language Model (LLM)
The type of AI model, such as GPT or Gemini, trained on vast text data to understand and generate human-like language, and the technology behind most modern AI search and chat tools.
Multimodal Search
Search that accepts and processes more than one input type at once, such as an image plus a text question, increasingly common in AI-powered search apps.
Prompt
The input text a user gives an AI system to generate a response. How a brand’s content answers likely prompts directly affects whether it gets surfaced.
Retrieval-Augmented Generation (RAG)
A technique where an AI model pulls in real, current external content (like your web page) before generating an answer, rather than relying only on what it learned during training.
Semantic Search
Search that matches meaning and intent rather than exact keywords, letting engines return relevant results even when the wording differs from the query.
Source Attribution
How clearly an AI tool credits the original page or brand behind information it presents, a major factor in whether GEO efforts translate into visible brand mentions.
Structured Data for AI
Schema markup and clearly labeled content sections that make it easier for AI crawlers to extract accurate facts, definitions, and comparisons from a page.
Training Data
The large body of text and data an AI model learned from before it was deployed. Content published today generally will not appear in a model until a future training cycle or through live retrieval.
Zero-Click AI Answer
A search result where an AI-generated answer fully satisfies the user’s question, so they never click through to a website at all.
