Generative engine optimisation (GEO) is the work of being named when a buyer asks a generative engine such as ChatGPT or Perplexity which provider to choose. The term comes from a 2023 research paper on visibility in generative engine responses.
How is GEO different from SEO and AEO?
SEO earns rankings in the blue links of Google and Bing, and AEO earns the answer itself: the summary an AI writes in AI Overviews, featured snippets or inside ChatGPT and Perplexity. GEO earns the recommendation. That split is ORRJO's; the paper uses GEO more broadly, for visibility in generative engine responses to diverse user queries.
Compare all three in SEO vs AEO vs GEO, or see how ORRJO runs AEO and GEO.
Questions buyers ask
Who came up with the term generative engine optimisation?
Pranjal Aggarwal and five co-authors, including researchers from Princeton University and IIT Delhi, introduced it in the paper GEO: Generative Engine Optimization, submitted to arXiv on 16 November 2023 and accepted to KDD 2024. In their tests, GEO methods raised visibility in generative engine responses by up to 40%.
Can GEO guarantee that an AI tool names your company?
No. The paper's authors note that content creators have little to no control over when and how their content is displayed. ORRJO does not guarantee that AI engines will mention you, or where you will rank. Nobody can.
How do you measure GEO?
By share of voice: fix a set of buyer prompts, run them monthly on the same engines in a clean browser profile, and count who gets named. ORRJO's AI visibility audit never puts your name inside the questions. It costs £750 plus VAT, one off, walkthrough included.
Sources
- Aggarwal et al., GEO: Generative Engine Optimization, arXiv:2311.09735, checked 13 October 2026.