Generative Engine Optimization (GEO)
Also called: GEO
Generative Engine Optimization (GEO) is the practice of measuring and improving how AI answer engines — ChatGPT, Perplexity, Gemini, Google AI Overviews, AI Mode, and Copilot — represent a brand: whether they name it and cite its domain when buyers ask category questions.
Where classic SEO optimizes for a ranked list of blue links, GEO optimizes for the synthesized answer itself. The unit of success is not position on a results page; it is whether the model names your brand in the prose a reader sees and cites your domain among its sources.
GEO has two halves that are easy to confuse. The input side (grounding, RAG, ontologies) shapes what your own AI knows. The output side — where Jincove works — reads what external engines actually said about you and turns each answer into evidence you can open, rather than a black-box score.
A practical GEO program picks the real questions buyers ask, runs them across the engines on a schedule, records the verbatim answer and its sources, and scores every answer on two booleans: mentioned and cited.
Start with the free audit
Send us one brand. We’ll run it through the engines and send back the answers, citations, and sources — so the first report your client sees is already backed by evidence.
Free audit: ChatGPT, Perplexity and Gemini, run by hand. Paid work covers all six engines.