Updated 2026-07-06
What is generative engine optimization (GEO)?
Generative engine optimization (GEO) is the practice of making a brand and its content more likely to be retrieved, cited, and recommended by AI answer engines — ChatGPT, Gemini, Perplexity, Google AI Overviews, and their peers. Where SEO optimizes for a ranked list of links, GEO optimizes for inclusion in a synthesized answer.
Definition
GEO covers everything that influences how generative engines answer questions in your category: whether your pages are retrievable and citable, whether your brand is named and recommended, how you are framed against competitors, and whether the facts the engine states about you are correct.
GEO vs SEO
The overlap is real — crawlability, content quality, and authority feed both. The difference is the unit of competition: SEO competes for positions on a results page; GEO competes for a handful of citation slots and mentions inside one answer. An answer engine may cite three sources where a results page listed ten links, and it may name brands without linking anyone at all. GEO vs SEO covers what carries over and what doesn't.
How GEO is measured
You can't measure GEO from your own analytics, because most AI answers send no traffic. Measurement means asking the engines your buyers' questions repeatedly and scoring the answers — prompt monitoring. The core metrics are citation rate, brand-mention rate, share of voice, and sentiment.
- Optimizes for inclusion in AI answers, not position in link lists.
- Competes for citation slots (linked sources) and brand mentions (named in the answer).
- Measured by monitoring prompts across engines, not by web analytics.
- Improved by citable content structure, entity consistency, and crawlable pages.
Where to start
Pick the prompts that decide deals in your category, measure where you stand on each platform, then close the gaps with content built to be cited. The full framework is in What is GEO? A practical guide.