The GEO Glossary

GEO — Generative Engine Optimization

The practice of structuring content and digital presence so AI answer engines cite, quote and recommend your brand. The term was coined in a Princeton study and is used by Search Engine Land, Coursera, Seobility and most 2026 industry coverage (Wikipedia).

AEO — Answer Engine Optimization

A near-synonym for GEO. Some practitioners use AEO specifically for optimization aimed at answer-style responses (Google featured snippets, People Also Ask, AI Overviews) and reserve GEO for the broader generative-model surface (Progress Sitefinity). No academic consensus separates them (Wikipedia).

LLMO — Large Language Model Optimization

Another synonym. Emphasizes optimization for the LLMs themselves (ChatGPT, Claude, Gemini) rather than the search-adjacent surface. Nikhil Lai of Forrester Research argued in 2025 that AEO, LLMO and related terms are “significantly, but not fundamentally, different from SEO” (Wikipedia).

AIO — AI Optimization

The broadest catch-all. Some vendors use “AIO” to cover any optimization of digital presence for AI systems, including chatbots that aren’t strictly answer engines.

AI Overviews

Google’s AI-generated summaries that appear above the traditional blue links. Reach more than 2 billion monthly users and are triggered on 18% of commercial queries and 14% of transactional queries as of late 2025 (Search Engine Land, Onely).

RAG — Retrieval-Augmented Generation

The architecture behind most modern answer engines. When a user asks a question, the system retrieves candidate documents from an index or the live web, then a language model generates an answer grounded in those documents and optionally cites them. GEO is largely about making your content retrieve well and generate well (Search Engine Land).

Embeddings

Numeric vector representations of text that let retrieval systems compare “meaning” rather than exact keywords. Answer engines embed both user queries and candidate content chunks, and pull the closest matches. Short, self-contained paragraphs embed more cleanly than sprawling ones — which is why “chunk hygiene” matters for GEO.

Chunks

The unit of retrieval. Answer engines typically split pages into 300–800 character chunks and index each chunk separately. Design your paragraphs to survive being lifted out of their surrounding context.

Entities

People, places, organizations, products and concepts that AI systems track as first-class objects. Using consistent names and sameAs links across pages helps engines disambiguate your brand and connect it to other authoritative sources (eSEOspace).

E-E-A-T

Experience, Expertise, Authoritativeness, Trustworthiness. Originally a Google search-quality framework; AI citation analyses consistently find E-E-A-T signals matter more for AI citations than for classical rankings (Stackmatix).

llms.txt

A proposed plain-text or Markdown file at your domain root, analogous to robots.txt, that offers AI systems a curated map of your important pages. Google has stated llms.txt alone doesn’t currently affect Search ranking (Contentful); other engines are experimenting with it.

IndexNow

A push-notification protocol supported by Bing, Yandex, Seznam and others that lets you notify search engines the moment content is created or updated (bing.com/indexnow). Useful for GEO because recency is a citation signal.

Schema.org

The shared vocabulary for structured data used by Google, Microsoft, Yandex and increasingly by AI systems. Deployed as JSON-LD in a <script> tag. Key types for GEO: Article, FAQPage, HowTo, Organization, Person, BreadcrumbList.

JSON-LD

The JSON-based syntax for Schema.org data. Preferred over Microdata and RDFa because it lives in a separate <script> block and is easier to author, validate and version.

Citation rate

The share of AI-generated responses that reference your domain, measured across a defined prompt panel. Strapi defines it formally as SUM(is_cited) / COUNT(*) over a rolling 30-day window (Strapi).

Zero-click search

Queries where the user gets the answer without clicking any result. Rose from 57–60% in 2023 to 68–72% in 2026, and climbs to 83% on queries with AI Overviews (Onely). The metric GEO is designed to counteract.

Share of voice

Your citations divided by total citations across every response for a category of prompts. The GEO equivalent of “market share” — and a much better business metric than raw ranking position.