What is generative engine optimization?
Generative engine optimization (GEO) is the practice of optimizing your content, structure, and signals so generative AI systems, including ChatGPT, Claude, Perplexity, and Google AI Overviews, can retrieve your information and cite it accurately in their answers.
Where classic SEO competes for a ranked link a person clicks, GEO competes to be the source an AI synthesizes into its response. The surfaces differ, but both reward the same thing: clear, trustworthy, well-structured content that genuinely answers the question.
How AI assistants choose what to cite
Most AI answer engines combine a language model with retrieval: they search the live web or an index, pull candidate passages, and synthesize an answer with citations. To be cited, your content has to be crawlable, retrievable for the query, and clearly the best available answer.
Three things must line up: the assistant can access your page, it can match your content to the question, and your content states the answer plainly enough to quote. Pages that bury the answer in fluff or hide it behind scripts rarely make the cut.
GEO starts with strong SEO
There is no GEO without crawlable, well-structured pages. AI systems rely on the same fundamentals as search: clean HTML, descriptive titles and headings, fast load times, logical internal links, and accurate metadata.
If a page cannot be crawled and understood by a search engine, it almost certainly cannot be retrieved and cited by an AI assistant. Fix technical SEO first, then layer GEO-specific tactics on top.
- Crawlable, server-rendered content rather than JavaScript-only rendering
- Descriptive titles, headings, and URLs
- Fast Core Web Vitals and clean internal linking
- Accurate, unique meta descriptions
Write answer-ready, citable content
AI assistants prefer content that states the answer up front, then supports it. Lead with a direct definition or conclusion, use clear headings phrased as questions, and keep claims specific and verifiable. Add original data, examples, and clearly attributed sources where you can.
Structure helps machines parse meaning. Use FAQ sections, step-by-step lists, comparison tables, and definition blocks. The easier it is to lift a clean, correct passage from your page, the more likely an assistant is to use it.
Strengthen entities and structured data
AI systems reason about entities, including your company, services, people, and topics, and how they relate. Consistent naming, an authoritative About page, and structured data such as Organization, Service, FAQ, Article, and DefinedTerm schema help assistants understand who you are and what you do.
Consistency across your site and the wider web matters too. The same business name, description, and core facts repeated accurately across pages and profiles strengthen the entity an assistant associates with your brand.
Add an llms.txt context file
An llms.txt file is a plain-text summary at the root of your domain that points AI systems to your most important, canonical pages with short descriptions. It is an emerging convention rather than a guaranteed ranking factor, but it is a low-cost way to offer machines a clean map of your site.
Pair it with an expanded context file and a preferred-citation sentence so assistants have an accurate, concise description to quote. Think of it as the press kit you hand to an AI.
How to measure GEO
GEO is harder to measure than rankings because answers are personalized and often clickless. Track whether your brand appears and is cited in AI answers for your priority questions, monitor referral traffic from AI tools, and watch for branded search lift as assistants surface your name.
Run periodic prompt audits: ask the major assistants the questions your buyers ask and record whether you are mentioned, cited, and described accurately. Treat misattributions as bugs to fix with clearer content and stronger entities.