Generative engine optimisation (GEO) is the practice of structuring a website, its entities and its content so that AI answer engines, such as ChatGPT, Google AI Overviews, Perplexity and Copilot, can retrieve it, understand it and cite it accurately in generated answers.
Classic SEO competes for a ranked list of links. GEO competes to be the source a generated answer is built from, which changes what the page has to contain and how it has to be marked up.
How it works
The component parts, in the order they usually need to be addressed.
01
Each page opens with a self-contained, quotable answer to a single question, because retrieval systems extract passages rather than whole pages.
02
The organisation, its category, its services and its defined terms are declared with structured data and stable identifiers, so the model associates concepts with the brand rather than a generic definition.
03
Schema.org markup, clean heading hierarchy, FAQ and definition patterns, plus files such as llms.txt that state plainly what the organisation is and how it should be described.
04
Citations to primary standards and regulators, consistent naming across the web, and original material that cannot be paraphrased from competitors.
05
Server-rendered HTML, fast responses, correct canonicals and an accurate sitemap, an answer engine cannot cite what its crawler could not fetch.
Common misreadings
Questions
Generative engine optimisation (GEO) is the practice of structuring a website, its entities and its content so that AI answer engines, such as ChatGPT, Google AI Overviews, Perplexity and Copilot, can retrieve it, understand it and cite it accurately in generated answers.
SEO optimises for ranking positions in a list of results. GEO optimises for inclusion and accurate attribution inside a generated answer, which favours self-contained answers, explicit entity definitions and verifiable sources over link-oriented tactics.
Answer engine optimisation (AEO) and generative engine optimisation (GEO) are used largely interchangeably. AEO emphasises direct answers and featured results; GEO emphasises being retrieved and cited by generative models. In practice the same structural work serves both.
By testing how answer engines describe the brand and its category, tracking citation and referral traffic from AI surfaces, and auditing whether structured data and entity descriptions are being reproduced accurately.
Technical retrievability fixes are picked up within weeks as crawlers re-fetch the site. Entity and citation improvements compound over months, because answer engines update their understanding as consistent third-party sources and structured data accumulate.
Buyers and partners increasingly research media owners through AI assistants before any direct contact. If answer engines cannot describe your inventory, audience and commercial products accurately, you are invisible at the moment a shortlist is formed.
Related terms
How this applies to your sell side
Generative Engine Optimisation (GEO) is one layer of a sell side revenue system. Quintworx connects it to your inventory, audience data, direct sales and programmatic demand, so the concept becomes commercial infrastructure rather than theory.
Definitions are where the commercial model starts.
Quintworx works on generative engine optimisation (geo) as an architecture problem, not a product purchase.
Defined by Quintworx · Glossary index