Guide · 6 min read · 2026-10-12
What is generative engine optimization (GEO)?
A clear definition of GEO, how AI answers choose products, and how GEO relates to SEO, for SaaS founders and marketers.
The short definition
Generative engine optimization (GEO) is the work of earning mentions in AI-generated answers. When a buyer asks an assistant "what's the best help desk for a 5-person team?", GEO is about whether your product is in the answer, how high, and how it's described.
How assistants build a recommendation
For buying questions, assistants with web search retrieve a handful of pages, often review grids, "best X" roundups, Reddit threads and vendor comparison pages, and then summarise the consensus. Products that appear across several trusted sources get named; products that appear on none don't.
Model training data adds a second layer: well-known brands are named even without retrieval. New products have to win through the retrieved sources.
GEO vs SEO
- SEO optimises your pages to rank. GEO optimises your presence across the sources the answer is built from, including pages you don't own.
- SEO measures positions and clicks. GEO measures mention rate, position in the answer and share of voice against competitors.
- SEO and GEO share foundations: crawlable pages, clear titles, structured data and authority.
The GEO loop
- 01Measure: run unbranded buyer prompts and record mentions, positions, competitors and cited sources.
- 02Prioritise: rank cited sources by frequency and pick the ones you can influence.
- 03Act: earn reviews, pitch roundups, publish comparison pages, clarify positioning.
- 04Track: rerun the same prompts weekly and watch share of voice.
Common mistakes
- Testing your brand name instead of the buyer's question.
- Judging from one answer. Outputs vary between runs.
- Writing more blog posts when the answer cites G2 and Reddit, not blogs.
- Vague positioning that doesn't map to a category.