- Generative Engine Optimisation (GEO)
- The practice of optimising a business's online presence so AI assistants like ChatGPT, Claude, Perplexity, and Gemini recommend and cite that business when users ask questions. GEO focuses on entity signals and structured data rather than blue-link rankings.
- Answer Engine Optimisation (AEO)
- A subset of GEO focused on restructuring page content into question-first, answer-first formats that AI assistants can extract cleanly as direct answers and citations.
- Large Language Model (LLM)
- An AI system trained on vast amounts of text to generate human-like responses. ChatGPT, Claude, Gemini, and Perplexity are all powered by LLMs that build internal entity graphs to decide which businesses to recommend.
- Entity Graph
- The internal knowledge structure an LLM uses to connect business names to services, locations, reviews, and authority signals. Strong, consistent entity signals across the web cause an LLM to recommend a business more often.
- llms.txt
- An emerging plain-text file at the root of a website that tells AI crawlers which content is most important and how to understand the business. Similar to robots.txt but aimed specifically at large language models.
- AI Overview
- Google's AI-generated summary at the top of search results for many queries. AI Overviews can answer a user without any link click, making AI Overview visibility a critical GEO outcome.
- Retrieval-Augmented Generation (RAG)
- A technique where an AI assistant fetches live web content at query time and uses it to ground its answer. Perplexity and ChatGPT Search both use RAG, which is why fresh, well-structured content is so important for GEO.
- Knowledge Graph
- A structured database of real-world entities (people, places, businesses) and their relationships. Google's Knowledge Graph powers Gemini's local business recommendations and feeds rich results across Google Search.
- Schema Markup (Structured Data)
- JSON-LD code embedded in a page that gives machines unambiguous facts about a business — services, locations, FAQs, reviews. The cleanest schema is the easiest for LLMs to ingest and cite.
- Zero-Click Conversion
- A customer outcome (call, enquiry, booking) that happens without the user visiting the website, because an AI assistant or AI Overview surfaced the business's phone number, service, and area directly in the answer.
- The complete set of places across the web where a business is mentioned by name. LLMs weight citation footprint heavily as a credibility and authority signal, even when the mention is not a clickable backlink.
- E-E-A-T
- Experience, Expertise, Authoritativeness, and Trustworthiness — the framework Google and most LLMs use to weight a source's credibility. Named-author content, transparent business details, and verifiable credentials all lift E-E-A-T.