What is generative engine optimization (GEO)?

GEO, short for generative engine optimization, is the practice of structuring a site's content so the language models behind ChatGPT, Perplexity, Google AI Overviews or Gemini can extract, understand and cite it correctly. It does not replace SEO; it sits on top of it.

The practical difference from SEO

Classic SEO chases a position in a list of results. GEO chases being the source the answer is built from. In the first case the link matters; in the second, what matters is whether your sentence can be lifted as it stands, without ambiguity.

What works

• A direct answer in the first paragraph, before context and preamble.

• Headings that reproduce the user's real question rather than a marketing slogan.

• Lists and tables: easier to extract than long prose.

• Concrete numbers, ranges and thresholds a model can cite without inventing them.

• Structured data: Organization, Service, FAQPage, Article, Breadcrumb.

• A visible author and date, because models prefer identifiable sources.

What does not work

• Long copy that delays the answer until halfway down the page.

• Superlatives without figures: nobody can cite "the best solutions".

• Identical content machine-translated across several languages.

• Important information hidden inside images or late-loading components.

How to check whether it works

1. Collect the real questions customers ask, in their own phrasing.

2. Put the same questions to ChatGPT, Perplexity and Google, and note who gets cited.

3. Publish one page per question, with the complete answer at the top.

4. Repeat the check monthly; results shift faster than in classic SEO.

5. Track referral traffic from generative engines separately, where it is identifiable.

What still holds from SEO

A site a crawler cannot read will not appear in generated answers either. Indexing, speed, URL structure, hreflang and structured data remain the foundation. GEO is the content layer built on a healthy technical base.