GEO, in full generative engine optimization, is optimising your content and your brand so that generative AI systems — ChatGPT, Gemini, Perplexity, Claude and Google AI Overviews — mention and cite you when someone asks a question you have the answer to. Where SEO is about a position in a list of links, GEO is about being part of one composed answer. This article explains what GEO is exactly, how it differs from SEO, AEO and LLMO, how generative engines choose their sources and how you get started.
What exactly is GEO?
Generative engine optimization is the umbrella term for everything you do to appear more often, and better, in answers generated by AI. The term emerged when search changed: instead of a list of ten links, a user increasingly gets a written answer with a few sources underneath. Whoever is in that answer gets the attention; whoever is not, briefly does not exist for that user.
A generative engine is any system that writes an answer instead of listing results. That includes chat assistants such as ChatGPT and Claude, answer engines such as Perplexity, and the AI layers in Google: AI Overviews at the top of the results and AI Mode as a fully conversational search experience. They differ in the details, but work on the same principle: retrieve, select, summarise, cite.
GEO targets two things at once. First, your pages: are they retrieved, and are they written so that the engine wants to use them as a source? Second, your brand: does the underlying model know your name, does it know what you stand for and is it willing to recommend you?
GEO, SEO, AEO and LLMO: what is the difference?
The terms get mixed up, and partly for good reason: the work overlaps. Still, it helps to keep them apart.
| Term | What it is about | Where you see it | How you measure it |
|---|---|---|---|
| SEO | Ranking in classic search results | Google, Bing: list of links | Positions, clicks, organic traffic |
| AEO | Delivering a direct answer to a question | Featured snippets, People Also Ask, voice assistants | Snippet share, zero-click visibility |
| GEO | Being mentioned and cited in generated answers | ChatGPT, Perplexity, Gemini, AI Overviews, AI Mode | Mentions, citations, share of voice per engine |
| LLMO | What the model knows about your brand without searching | Answers without sources, recommendations | Brand mentions on recommendation questions |
SEO is the foundation: an engine that cannot find your page cannot cite it. AEO is the writing style: answer first, explanation after. GEO is the broader goal, and LLMO is the long-term part of it that you only influence through consistency and reputation.
How generative engines choose their sources
Almost every generative engine works with retrieval-augmented generation. For a question, the system first looks up a set of candidate pages — through its own index or through a classic search engine. Those pages are cut into chunks and compared to the question by meaning, using vector embeddings. The chunks that fit best go to the model as context; the model writes an answer from them and lists the chunks it used as sources.
The things that matter follow from that process. Selection happens at passage level, not page level: one strong paragraph can be cited from an otherwise mediocre page, and a long page without a clear answer is skipped. Factual, specific text beats general text, because the model can write general text itself and only needs your page for what it does not know. Freshness counts, especially for questions that refer to 'now' or 'this year'. And consensus counts: if several independent sources say the same thing about you, the model is more confident it is true.
What does not happen is just as important: the engine usually does not execute JavaScript and does not wait for slow pages. Content that only appears after a script runs is not included — one of the most common reasons online stores and SaaS sites are missing from AI answers.
The six principles of GEO
The work can be summarised in six principles that recur in every engine.
One: answer first. Every page and every section opens with the definition, the advice or the number, and explains afterwards. Two: one question per block. Use headings that ask a question or name a sub-topic, followed by a compact, self-contained answer that can be understood without the rest of the page. Three: facts and entities. Name names, versions, prices, quantities and dates, and consistently use the same name for your brand, your products and your categories. Four: evidence. Point to sources, your own data or examples; a claim without support is worth no more to a model than a competitor's claim. Five: freshness. Update pages, show the last-updated date and remove what no longer holds. Six: consistency beyond your site. Make sure directories, partners, reviews and media say the same about you as you do, so the model builds an unambiguous picture of your brand.
These principles are not tricks. They simply describe content that is pleasant for a reader and usable for a machine. That is exactly why GEO and good SEO rarely conflict.
What GEO is not
GEO is not a separate website or a separate set of pages 'for AI'. The same pages serve visitors, Google and generative engines. GEO is also not a matter of hidden text, instructions to the model or mass-generated pages; those tactics are recognised and cost you more than they deliver. And GEO is not a guarantee: engines choose per question and per run, so you steer on odds and trends, not on a fixed spot.
How to measure GEO
Because answers vary from run to run, you measure with prompt sampling: a fixed set of questions you ask each engine repeatedly. Pick questions your customers really ask — informational questions, comparisons and recommendation questions — in their own language. Record per answer whether your brand is mentioned, whether one of your pages is cited, in what wording and which competitors appear next to you. From that, calculate your share of voice per engine and follow the trend month by month.
You do not have to do a first measurement by hand: the free AI visibility check asks a set of questions to ChatGPT, Gemini and Perplexity and shows whether you or your competitor gets mentioned. How we measure and why we do not work with a single 'AI score' is in our methodology.
Where do you start?
Start with a baseline: twenty to fifty questions, three engines, one round. That immediately shows where you are missing while a competitor is mentioned. Then check the technology: is your content in the HTML, do pages load fast, and are the AI bots not accidentally blocked in robots.txt? Next, rewrite the pages closest to the questions according to the six principles: answer first, one question per block, facts, evidence, freshness. Then expand with the questions you do not have a page for yet, and work on your brand beyond your site in parallel. Measure again every month.
Conclusion: GEO is SEO for a world of answers
GEO does not change what good content is, but it does change what you want to achieve with it: not a click from a list, but a place in the answer itself. Whoever makes their pages reachable, writes them as answers and builds their brand consistently gets cited more often — in Google and in AI answers. If you want to tackle this structurally without pulling on it yourself every month, Traze measures and improves it per engine for you; see how our AI visibility (GEO) works.