What is Generative Engine Optimization (GEO)?

Generative Engine Optimization (GEO) is the practice of making content easy for AI answer engines — ChatGPT, Claude, Gemini, Perplexity, and Google's AI Overviews — to retrieve, trust, and cite when they answer a question.

Why it matters

Traditional SEO optimises for a ranked list of links a person then clicks. AI answers rarely produce that list: the engine reads a handful of sources and writes a single response, naming only some of them. If your page is not among the sources it retrieves, you are not merely ranked lower — you are absent from the answer entirely, and the user never learns you exist.

How it works in practice

GEO and SEO overlap far more than the framing suggests. An engine still has to find, crawl, and parse the page, so crawlability, server-rendered HTML, clean headings, and structured data remain prerequisites rather than legacy concerns. A page that needs JavaScript to render its content is invisible to most AI crawlers, which do not execute it.

Where the two diverge is what happens after retrieval. Ranking rewards a page that comprehensively covers a topic; citation rewards a passage that answers one question cleanly enough to be lifted. That favours self-contained sections with an explicit question as the heading, a direct answer in the first sentence, and specific verifiable claims — numbers, dates, named sources — over hedged summary prose.

Two things sit outside the page itself. Crawler access is a gate: robots.txt directives for GPTBot, ClaudeBot, CCBot, and Google-Extended decide whether your content can enter a model's training data or grounding index at all, and blocking them removes you from consideration regardless of quality. And because engines synthesise across sources, being described consistently elsewhere — the same category language, the same claims — makes a brand easier to reconcile as one entity.

Also called: GEO, generative engine optimisation, AI search optimization.