GEO vs SEO: what really changes, and what does not

Those who have done SEO for years tend to read GEO as a new acronym for the same things: quality content, structured data, authority. Partly true, and partly a mistake that costs dearly. This article lines up what stays the same and what changes, with the data.

What stays the same

A technically sound website is the base of both. The generative engines that browse the web read indexed pages: if Bing or Google cannot see you, neither can ChatGPT or Gemini. Sitemaps, canonicals, speed, HTML readable without JavaScript remain necessary, and schema.org structured data, which help machines understand what is on a page, remain useful.

The underlying principle also stays: machines reward those who answer a question well. What changes is how the answer is used.

What changes: the goal

SEO works to appear among the results: a list of links, from which the user chooses. GEO works to appear inside the answer: a single text, written by the model, in which the user chooses nothing. The list has ten slots; the answer has three or four names, on average.

This difference explains the most cited figure of 2026: fewer than 10% of the sources cited by ChatGPT, Gemini and Copilot appear on Google's first page for the same question. Ranking first on Google does not guarantee being cited, and not ranking does not prevent it. The two systems select with different criteria.

What changes: the unit of work

SEO optimises pages: every URL competes for its own keywords. GEO optimises entities: the company, the person, the product, and the set of sources that talk about them. The model does not ask "which page answers best", but "what do I know about this company and from where". Consistency across sources weighs more than the quality of a single page.

That is why the most important GEO intervention is almost never on the website: it is on Wikidata, LinkedIn, category directories, reviews, press, communities. For traditional SEO these are "off-site signals"; for GEO they are the raw material.

What changes: the selection criteria

Studies of model behaviour, starting with the Princeton one that coined the term GEO in 2023, indicate that the passages picked up in answers have recognisable features:

• they contain statistics with source and date;
• they contain quotations from identifiable people;
• they are self-contained: understandable without reading the rest of the page;
• they sit in the first third of the page (almost half of citations come from there);
• they are consistent with what other sources say about the same entity;
• they are recent, or at least dated.

None of these criteria concerns keywords. A page written to rank for "best ERP software" can be irrelevant to a model looking for a verifiable fact about a company.

What changes: the measurement

SEO is measured in rankings, impressions and clicks. GEO is measured in presence, accuracy and sentiment in answers, per question and per engine, and in share of voice: who is cited next to you. There is no stable "position 1": there is the frequency with which you appear when the question is repeated. That is why the GEO Assessment uses fixed sets of repeated questions and compares before and after.

AEO, LLMO and the other acronyms

AEO (Answer Engine Optimization) stresses direct answers, LLMO (Large Language Model Optimization) the models, GEO the generative engines. In practice they refer to the same field. The acronym matters little; what matters is understanding that the variable is no longer the page but the entity.

What to do if you already have an SEO strategy

Keep it, and add three things: a measurement of what the AI engines answer today, a source map of what shapes them, and a plan of interventions on third-party sources. The fastest way to start is the free 48-hour audit; to go deeper, the GEO guide.