Glossary · 13 terms
GEO terms, defined plainly.
GEO introduces terminology that overlaps with but is distinct from traditional SEO. These 13 core concepts appear throughout the playbook — from readiness levels to the technical protocols underpinning Phase 4.
TL;DR
GEO introduces a set of terms that overlap with but are distinct from traditional SEO. This glossary defines the 13 core concepts used throughout the playbook — from the readiness ladder levels to the technical protocols (WebMCP, llms.txt) that underpin Phase 4. New to GEO? Start here before reading the phases.
Why this matters: GEO terminology is evolving fast and often misused. Precise definitions matter when briefing developers, writing content briefs, or evaluating vendor claims.
- GEO (Generative Engine Optimisation)
- The practice of making a website discoverable, citable, and transactable by AI-powered search and recommendation systems — the counterpart to traditional SEO for the LLM era.
- AEO (Answer Engine Optimisation)
- A subset of GEO focused specifically on getting your content quoted as a direct answer by AI systems like ChatGPT, Perplexity, or Google AI Overviews.
- LLM / AI crawler
- An automated bot operated by an AI company (e.g. GPTBot, ClaudeBot, PerplexityBot) that fetches and indexes web content to train or augment large language models.
- llms.txt
- An emerging open standard (similar to robots.txt) that lets site owners declare AI-specific access rules and link to key content for LLM consumption, placed at the root of a domain.
- robots.txt
- A plain-text file at the root of a domain that instructs crawlers which pages they may or may not access; AI crawlers respect it just like traditional search bots.
- Schema.org / structured data
- A shared vocabulary of JSON-LD markup embedded in HTML that tells search engines and AI systems what a page is about — product, FAQ, organisation, article — in a machine-readable format.
- RAG (Retrieval-Augmented Generation)
- An AI architecture where a model fetches live documents at query time to ground its answer in current facts, rather than relying solely on training-time knowledge.
- Citation
- When an AI system names or quotes your brand, product, or content in a generated answer — the primary success metric of GEO, equivalent to a top-ranking organic result in traditional SEO.
- Readiness ladder
- Hidden Layer's five-level framework (L0 Invisible → L4 Transactable) describing the sequential stages of AI readiness, where each level depends on the one below it.
- Render gap
- The discrepancy between what a browser displays (after executing JavaScript) and what an AI crawler actually sees (server-rendered HTML only), often causing LLMs to miss core page content.
- Entity
- A uniquely identified real-world concept — a brand, product, or person — that AI systems track across sources using @id anchors and sameAs links to resolve facts about it.
- WebMCP
- An open protocol that lets browser-based AI agents discover and invoke HTML forms as tools via data-toolname / data-tooldescription attributes and a /.well-known/webmcp manifest.
- Cold recall
- The ability of an LLM to accurately describe your brand from training data alone, without any retrieval or search — measured by Hidden Layer's geo_cold_recall score and the primary signal of long-term GEO progress.