What is GEO?

GEO (Generative Engine Optimization) is the practice of shaping your online presence so that generative AI models — the ones powering ChatGPT, Claude, Gemini, and similar tools — describe, cite and recommend your brand accurately and favorably.

A growing share of research and buying decisions now start with a question typed into an AI assistant instead of a search box. When that happens, the model synthesizes a single answer rather than returning a page of links to sort through. If your brand isn't part of that answer, you don't get a lower spot on the page — you don't appear at all. GEO is the discipline of making sure that doesn't happen by default.

GEO shares some overlap with SEO — clear, well-structured, factual content still matters — but the goal is different. SEO optimizes for ranking in a list of links. GEO optimizes for being named, accurately described, and recommended inside a generated answer, where there's often room for only a few brands to be mentioned at all. A page can rank well in Google and still be completely absent from an AI-generated summary of the same topic, because the model is synthesizing an answer rather than listing sources.

Different engines work differently, but most combine two things: what the underlying model already "knows" from its training data, and — for engines that browse or retrieve in real time — what it can find and cite from the live web right now. That's why the same brand can be described differently across engines, and why sources that are frequently cited, well-structured and easy to reference tend to show up more often in the answers those engines generate.

• Understanding which prompts in your category generate AI answers
• Tracking whether your brand appears in those answers, and how
• Identifying the sources AI models cite most, and getting cited by them
• Publishing content that directly answers high-intent buyer questions
• Making sure independent sources — reviews, comparisons, press — describe you accurately and consistently
• Monitoring how competitors are mentioned in the same answers, not just your own visibility

Say someone asks an AI assistant "what's a good tool for [your category]?" The model doesn't run a search and hand back ten links — it picks a small number of brands to mention, usually the ones it has the most confident, consistent information about from training data and cited sources. If your brand rarely appears in the sources that shape that confidence — comparison articles, review sites, documentation other people link to — you're less likely to be one of the names it reaches for, regardless of how well-known you are among your actual customers.

• Treating it as a keyword exercise instead of focusing on clear, factual, easy-to-cite content
• Checking one AI engine once and assuming that result holds everywhere and over time
• Ignoring the independent sources — reviews, comparisons, forums — that AI models often trust more than a brand's own website
• Optimizing only branded prompts and missing the category and comparison questions that shape consideration earlier
• Making changes without a way to measure whether mentions, position or citations actually moved

GEO and AEO overlap heavily and are often used interchangeably. If there's a distinction, AEO tends to focus more narrowly on structuring content to directly answer specific questions, while GEO covers the broader discipline of shaping how generative AI models represent your brand across many conversations. Read more in What is AEO?.

MentioningYou tracks your GEO performance across every major AI engine — visibility, share of voice, citations and sentiment — and turns the gaps into prioritized actions.