GEO Glossary: Key Terms in Generative Engine Optimization

This glossary defines the core concepts behind Generative Engine Optimization: the signals, metrics, and systems that determine how AI platforms cite brands in generated answers.

Generative engine optimization is a new enough discipline that its vocabulary is still being established. Terms like "entity signals," "AI citation," and "Share of AI Voice" are used across the industry in inconsistent ways. The definitions here reflect how these concepts are applied in practice across AI visibility audits, and how they connect to measurable improvements in how AI platforms name and describe brands.

If you're new to GEO, start with the foundational concepts below before working through the individual terms.

Foundational concepts

What Is Generative Engine Optimization (GEO)? Foundation

GEO is the full-stack practice of improving how often your brand is cited, mentioned, and accurately described in AI-generated answers, covering entity signals, schema markup, content structure, and third-party validation.

What Is Answer Engine Optimization (AEO)? Foundation

AEO is the content-layer component of GEO: the practice of structuring pages so AI systems can extract and cite them when generating direct answers to buyer questions.

What Is an Entity in GEO? Foundation

An entity is a company, product, or concept that AI systems can recognize, verify, and confidently describe using multiple independent sources. It is the foundational requirement for consistent AI citation.

Signals and infrastructure

What Are Entity Signals? Technical

Entity signals are the external profiles, database entries, reviews, and press mentions that allow AI systems to verify a brand independently of its own website, including G2, Capterra, Crunchbase, Wikipedia, and Google Business Profile.

What Is Schema Markup? Technical

Schema markup is machine-readable JSON-LD code added to a website that tells AI crawlers and search engines exactly what a page or organization is, turning unstructured content into verified, citable facts.

What Is Retrieval-Augmented Generation (RAG)? Technical

RAG is the architecture used by platforms like Perplexity AI that performs a live web search before generating an answer, making recently indexed, well-structured content influential on citation outcomes faster than training-data-dependent platforms.

Measurement and outcomes

What Is AI Visibility? Metric

AI visibility is the overall measure of how consistently and accurately a brand appears across AI-generated answers. It is the top-level metric that citation rate, mention position, and answer accuracy all feed into.

What Is an AI Citation? Metric

An AI citation is when an AI system names or references your brand in a generated answer. It is the unit of measurement that determines AI visibility, tracked by citation rate, citation position, and citation accuracy.

What Is Share of AI Voice? Metric

Share of AI Voice is the percentage of AI-generated answers your brand appears in relative to competitors. It is the competitive layer of AI visibility that tells you not just how often you're cited, but how you rank against the brands competing for the same buyers.

What Is Google AI Overviews? Platform

Google AI Overviews is the AI-generated summary that appears above traditional search results on many Google queries. It is the platform most influenced by FAQPage schema and Google's entity graph, and the fastest to respond to technical GEO improvements.

Frequently Asked Questions

• What is a GEO glossary?

  A GEO glossary is a reference for the vocabulary of generative engine optimization: the terms that describe how AI platforms decide which brands to cite in generated answers. The terms in this glossary cover the signals, metrics, and platforms relevant to improving AI visibility.

• What is the most important GEO term to understand first?

  Entity recognition is the foundational concept. Understanding what an entity is and why AI systems require independent verification to cite a brand confidently explains why GEO is a separate discipline from SEO and why search rankings alone do not translate into AI visibility.

• What is the difference between GEO and AEO?

  AEO (answer engine optimization) focuses on content structure: how directly pages answer buyer questions and whether that content is formatted for AI extraction. GEO covers everything AEO covers and adds entity signals, schema markup, and third-party validation. AEO is a component of GEO, not a replacement for it.

• Are these terms specific to one AI platform?

  No. The concepts in this glossary apply across ChatGPT, Perplexity, Claude, and Google AI Overviews. The specific signals that move each platform differ: Perplexity responds more to recently indexed content, ChatGPT weights historical entity authority, Google AI Overviews responds strongly to FAQPage schema. The underlying vocabulary covers all four.

• How do these terms connect to the AI Visibility Report?

  The AI Visibility Report tests and measures the outcomes described in this glossary: citation rate across platforms, entity signal completeness, schema markup coverage, and Share of AI Voice against named competitors. Each section of the report maps directly to the concepts defined here.