Every term you need to know about Generative Engine Optimisation, agentic selling, and the future of AI-driven business discovery.
The practice of deploying AI agents that actively promote and sell your business across AI platforms. Unlike passive GEO (which optimises for visibility), agentic selling uses autonomous AI agents to actively shape how AI systems perceive and recommend your business.
Google's AI-generated summary that appears at the top of search results, above traditional organic listings. AI Overviews reduce click-through to traditional search results by answering the user's query directly on the search page.
The degree to which your business is known, referenced, and recommended by AI systems. High AI visibility means AI frequently and confidently recommends your business for relevant queries. Low AI visibility means your business is invisible in AI conversations.
A systematic assessment of how major AI systems respond to queries relevant to your business. The audit tests whether AI recommends your business, what it says about you, and how your visibility compares to competitors.
Any data point that increases AI's confidence in recommending your business. Common authority signals include customer reviews, third-party mentions, industry certifications, directory listings, press coverage, and academic or professional citations.
The uniformity of your business information (name, address, phone number, services) across all digital platforms. AI systems cross-reference citations across sources, and inconsistencies reduce recommendation confidence.
The structure and organisation of your website content, optimised for AI parsing. Good content architecture uses clear headings, direct answers to common questions, proper schema markup, and logical information hierarchy that helps AI understand your business.
AI's ability to identify your business as a distinct entity with specific attributes: location, services, reputation, and relationships. Strong entity recognition means AI understands what your business is and what makes it distinct from competitors.
The practice of optimising your business's entire digital presence so AI systems confidently recommend it. GEO is the successor to SEO, addressing how businesses get discovered through AI assistants rather than traditional search engines.
Any AI system that generates responses to user queries, including ChatGPT, Claude, Gemini, Perplexity, and others. These engines generate recommendations rather than listing links, fundamentally changing how businesses are discovered.
JavaScript Object Notation for Linked Data — the preferred format for implementing schema markup on websites. JSON-LD provides AI systems with structured, machine-readable information about your business: what you do, where you are, your hours, services, reviews, and more.
A structured database of entities and their relationships that AI systems use to understand the world. Google's Knowledge Graph is the most well-known example. Being represented accurately in knowledge graphs is essential for AI visibility.
The AI technology that powers systems like ChatGPT, Claude, and Gemini. LLMs generate text responses based on patterns learned from vast amounts of training data, supplemented by real-time information retrieval. Understanding how LLMs work is fundamental to effective GEO.
Name, Address, Phone number consistency across all digital platforms. A foundational GEO requirement — if your NAP data is inconsistent across the web, AI systems lose confidence in your business information and are less likely to recommend you.
The way users find businesses through AI by asking questions in natural language (prompts) rather than typing keywords into a search box. GEO optimises for prompt-based discovery rather than keyword-based search.
A technique where AI systems retrieve real-time information from the web before generating their response. RAG means your current online presence directly influences AI recommendations, even if the AI wasn't trained on your data. This makes ongoing GEO essential.
The level of certainty an AI system has when recommending your business. Higher confidence leads to stronger, more specific recommendations. Confidence is built through consistent authority signals, positive reviews, and clear, accurate information across sources.
Structured data added to your website that tells AI systems exactly what your business is, what it offers, and how it should be categorised. Schema markup types include LocalBusiness, Product, Restaurant, ProfessionalService, and many others.
The traditional practice of optimising websites to rank highly in search engine results pages (SERPs). While still relevant, SEO's effectiveness is declining as users shift to AI-first discovery. GEO is the evolution of SEO for the AI era.
The vast corpus of text, web pages, and documents that an AI model learns from during its initial training. Your business's representation in training data influences how AI perceives you. While you can't directly control training data, you can ensure your digital presence is rich, accurate, and authoritative.
Any indicator that increases AI's trust in your business information. Trust signals include verified business listings, SSL certificates, consistent NAP data, professional association memberships, and long-standing web presence.
A response from an AI or search system that fully answers the user's question without requiring them to click through to a website. AI recommendations are inherently zero-click — the user gets an answer directly. This makes being the recommended business even more critical, as there's no "next result" to fall back on.
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