Generative Engine Optimization (GEO) has a fast-growing vocabulary — engines, metrics, crawlers and tactics that didn’t exist a few years ago. This glossary defines the terms you actually need to understand and measure your visibility inside AI answers, in plain language and updated for 2026.
The practice of optimizing your brand and content to be cited and recommended inside AI-generated answers — from ChatGPT, Gemini, Perplexity and Google AI Overviews — the way SEO optimizes for ranking in classic search results. It shares SEO’s technical foundations but adds tactics for being extracted and quoted by language models.
Optimizing to be the direct answer an “answer engine” returns, rather than one of ten blue links. In practice AEO and GEO are used interchangeably; GEO is the more common term in 2026. Both target the same goal: being the source the AI names.
Google’s AI-generated answers that appear above the classic results for many queries, synthesised from multiple sources and citing a few of them. Formerly associated with SGE (Search Generative Experience). Being cited in an AI Overview often matters more than the ranking beneath it.
The share of AI answers, across a defined set of buyer prompts, in which your brand appears versus your competitors. It’s the AI-era equivalent of share of search — a single number for how much of the AI conversation you own.
Three finer-grained metrics: share of answer is how often you’re the recommended option; share of citation is how often you’re a linked source; share of mention is how often your name appears at all. A brand can be mentioned without being cited, or cited without being recommended.
How frequently an AI engine cites your website as a source across a set of tracked prompts — usually expressed as a percentage. It measures whether your content is not just readable but actually used in answers.
The full set of real questions your buyers ask AI assistants in your category — the prompts you track to measure visibility. A well-built prompt universe covers awareness, consideration and decision-stage questions, not just your brand name.
Establishing your brand as a clear, well-defined entity (via consistent naming, structured data, Wikipedia/Wikidata presence and citations) so search and AI engines recognise what you are and confidently recommend you.
The difference between what a browser shows (after running JavaScript) and what a non-JS crawler like GPTBot or PerplexityBot fetches (the raw HTML). A large render gap means AI engines see a near-empty page even though users see a full one.
A proposed plain-text file at your domain root that points AI crawlers and assistants to your most important, citable pages — like a curated sitemap for LLMs. It complements robots.txt (which controls access) by guiding attention.
OpenAI’s two crawlers. GPTBot gathers data to train and improve ChatGPT; OAI-SearchBot fetches pages for ChatGPT’s live search and browsing. Allowing both in robots.txt is required to be read and cited by ChatGPT.
Perplexity’s crawler, which reads pages it may cite in its answers (shown in a visible “Sources” list). If it’s blocked or your content is JavaScript-only, Perplexity can’t use your site as a source.
A robots.txt control token that governs whether Google may use your content for Gemini and AI Overviews. It’s independent of Googlebot — blocking it doesn’t affect classic Search ranking, and allowing it doesn’t change indexing.
Content that leads with a direct, self-contained answer (a TL;DR) near the top of the page, before the supporting detail. It’s the single most reliable format for being lifted and quoted by AI engines and featured snippets.
Grounding means an AI engine bases its answer on retrieved sources (with citations) rather than only its training memory. It’s powered by RAG — retrieval-augmented generation — where the model fetches relevant documents at answer time. Grounded engines are exactly the ones GEO targets, because being retrievable gets you cited.
They’re largely the same thing. GEO (Generative Engine Optimization) and AEO (Answer Engine Optimization) both mean optimizing to be cited and recommended in AI answers. GEO is the more widely used term in 2026.
The share of AI answers, across a set of tracked buyer prompts, in which your brand appears versus competitors — a single metric for how much of the AI conversation you own.
The content a non-JavaScript AI crawler misses because your page only renders it after JavaScript runs. It makes your page look nearly empty to engines like GPTBot even though users see it fully.
A plain-text file at your domain root that points AI crawlers to your best, most citable pages — a curated index for LLMs that complements robots.txt.
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