Generative engine optimization is the practice of making a business more likely to be named and cited in answers produced by AI tools such as ChatGPT, Claude and Perplexity, where there is no results page and no click. It differs from answer engine optimization, which concerns AI features inside search itself, such as Google's AI Overviews. Both are built on the same technical and content foundations as traditional SEO, and the work diverges once those foundations exist.
Three terms, clearly separated
| Term | The surface | What decides whether you appear |
|---|---|---|
| SEO | A results page with ranked links | Relevance, authority, and the technical ability to be crawled |
| GEO | An answer from a tool you ask directly | How consistently your category describes you, across everything the model reaches |
| AEO | An AI summary at the top of a search results page | Ranking first, then being structured so a summary can use you |
The distinction between the last two matters because the work differs. AEO is gated by traditional ranking: if you are not in the set being summarized, nothing else applies. GEO is gated by corroboration, most of which sits on websites you do not control.
What makes a page usable by a generative engine
A model lifts a passage, strips the context around it, and presents it as an answer on its own. A paragraph that only makes sense after reading the three above it either goes unused or gets used wrongly.
- Claims stated plainly and early, before any warm-up.
- Each claim standing on its own, without leaning on the sentence before it.
- Attribution inside the sentence where a claim needs a source.
- Answers in text, not only inside a chart or an image.
- Headings that describe what sits under them, rather than teasing it.
- Structured data, so what the page is about does not have to be inferred.
The part that is not on your website
Generative engines draw on what they were trained on and, increasingly, what they retrieve while answering. That means how you are described elsewhere carries real weight: directories, industry publications, forums, review sites, anywhere your category gets discussed.
Being described consistently across those sources is slow work with no switch to flip. It is also the part that separates GEO from an ordinary content project.
What nobody can offer you
- A method that makes a model cite you on demand
- A reliable figure for what share of AI answers you appear in
- A replacement for SEO, given a page that cannot be crawled will not be quoted either
- Stable results, on surfaces that change without announcement
What exists is work that makes you a better candidate: clearer, better structured, better corroborated, more consistently described. Anyone promising more than that is selling certainty that does not exist yet.
How to get a baseline
- Write down the questions your buyers actually ask, in their words rather than yours.
- Ask them across the tools that matter to you, and record what comes back and who gets named.
- Note which sources the answers lean on. Those are the places worth being described well.
- Repeat it on a schedule. Direction across several samples tells you more than any single reading.
That is a sample rather than a measurement, and it should be labeled as one every time it is reported.
GEO runs on the same groundwork as SEO, with two things added: writing that survives being taken apart, and consistency in how the wider web describes you. Very little of it is new.