Generative engine optimisation (GEO) is the practice of structuring content to be retrieved and cited by generative AI models, including ChatGPT, Gemini, and Perplexity, when they compose answers to user queries.
Generative AI models do not return ranked lists. They compose answers, and they pull material from sources they deem credible, well-structured, and relevant. If your content is not written in a way that these models can extract and attribute, it is invisible in their responses even if it ranks well in traditional search.
GEO is the set of techniques that increases the probability a generative model will retrieve your content and cite it in its answer. The term was popularised by a 2023 paper from Princeton and Georgia Tech researchers, who found that certain content strategies, including adding statistics, citing authoritative sources, and leading sections with direct answers, increased citation rates in AI-generated responses by measurable margins.
No, not replacing: supplementing. SEO and GEO target different outputs. SEO targets a ranked position in a search engine results page. GEO targets a citation in a generative AI response. A brand that is strong at SEO but ignores GEO risks becoming invisible in the AI layer that sits above search results. A brand that optimises only for GEO without SEO foundations may find that AI systems, which draw on web-crawled content, have little material to retrieve in the first place.
The practical reality is that GEO success builds on SEO foundations. Pages that are crawlable, indexed, and trusted enough to rank tend to be the same pages that generative models retrieve. But ranking alone is not sufficient: a page structured for a crawler may still fail to be cited by a language model if it does not lead with direct answers, contain specific data, or use clear machine-readable structure.
GEO is a subset of answer engine optimisation (AEO). AEO is the broader discipline covering all AI-powered answer surfaces, including Google AI Overviews, voice assistants, and AI-integrated search. GEO focuses specifically on retrieval by generative models. In practice the strategies overlap almost entirely, but AEO is the more useful frame because it includes Google's AI Overviews, which remain the highest-traffic AI answer surface for most publishers. See AEO vs GEO for the full disambiguation.
Direct, answer-first structure. Generative models extract content in chunks. If the answer to the implied question does not appear in the opening lines of a section, the model may skip it. Every heading should be followed immediately by the direct answer to the question it implies.
Cited statistics and original data. The Princeton and Georgia Tech GEO study found that adding statistics increased citation rates by approximately 40% in their test set. AI models treat specific, verifiable numbers as a quality signal. First-party data, surveys, or test results are more valuable than references to third-party reports.
Authoritative sourcing within the text. Linking to primary sources, citing named studies, and attributing claims to named experts all increase the credibility signals that a generative model uses when deciding whether to cite a page.
Clear schema markup. FAQ, HowTo, and Article schema make the structure of a page machine-readable in a way that helps both traditional search crawlers and AI retrieval systems identify the key claims and their context.
Topical depth. A single well-optimised page is less likely to be cited than a cluster of related pages that together signal comprehensive expertise on a topic. Generative models weight topical authority, not just individual page quality.
GEO is not a licence to manufacture statistics or exaggerate expertise. AI systems, and increasingly the quality raters who evaluate them, are effective at identifying content that looks authoritative but is not. The consequences of getting flagged as low-quality are harder to recover from in the AI era than in the era of keyword penalties, because a model that associates your domain with low-quality content may deprioritise all of your pages, not just the one that triggered the signal.
GEO also does not mean writing for robots at the expense of human readers. The best-performing GEO pages are also, consistently, the pages that human readers find most useful. The discipline and genuine editorial quality are the same thing.
Related: What is answer engine optimisation? · How to get cited by ChatGPT
Quarrybank applies GEO principles at the brief stage, not as a retrofit: answer-first structure, specific data, and a quality gate before anything goes live.
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