What is Generative Engine Optimization (GEO)?

Why GEO matters now

Generative Engine Optimization (GEO) is the practice of shaping your content, entities and authority so generative AI systems surface and represent your brand accurately when they compose an answer. As tools like ChatGPT, Gemini, Perplexity and Google AI Overviews replace the list of links with a written response, the question is no longer "do you rank?" but "does the model include you when it writes?"

How generative engines assemble an answer

Generative engines don't return a page — they generate one. They retrieve trusted, well-structured sources, weigh them for relevance and authority, then synthesise a single response that names a small set of brands. GEO makes your content easy to retrieve, easy to quote, and unambiguous about who you are.

• Retrievable: clean, semantic content the model can find and parse.
• Quotable: self-contained paragraphs that stand alone as an answer.
• Trusted: entity clarity and citations that signal you're a credible source.

GEO vs AEO vs SEO

The three overlap but aim at different end-states. SEO optimises to rank a page. AEO (Answer Engine Optimization) optimises to be the cited source inside an answer. GEO is the broader discipline of being accurately represented across all generative AI output — citations, recommendations and the way models describe you. In practice we run them together. See AEO vs SEO and What is AEO?

How to optimise for GEO

Strong GEO rests on the same foundations we apply in every engagement: a clear entity (Organization and LocalBusiness schema, a consistent name, a Knowledge Graph presence), answer-ready content structured around real questions, and authority built through citations and mentions across the sources models trust — including LinkedIn, Reddit and Wikipedia-grade references.