The direct answer
Generative engine optimization, GEO, is the work of making a brand more likely to appear in the answers generative AI systems produce: named in a recommendation, cited as a source, or described accurately in a comparison. The engines in question include ChatGPT, Claude, Perplexity, Gemini, and Google's AI results.
The success metric is presence in answers. Rankings, impressions, and traffic remain useful signals, but GEO is judged by what the generated text actually says.
What the work looks like in practice
- Identify the buyer questions where an AI answer decides the shortlist.
- Audit who the engines currently name and which domains they cite for those questions.
- Publish content engines can lift: direct answers, question-led structure, self-contained passages.
- Build accurate presence on the sources those answers keep citing.
- Re-measure the same questions on a schedule and judge changes against normal answer variance.
What GEO is not
It is not prompt trickery, hidden text, or a way to inject your brand into other people's answers; engines retrain and re-retrieve, and gimmicks do not survive either. It is also not a paid placement, because none of these engines sell positions in organic answers.
And it is not rank tracking with a new logo: a rank describes a list, while GEO's unit of measurement is the generated answer itself.
Where to go deeper
This page is the short answer. The full generative engine optimization guide covers the mechanics, the measurement loop, and how GEO relates to the rest of the organic program.