Generative Engine Optimization (GEO)

Generative engine optimization (GEO) is the practice of structuring your content, brand signals, and technical setup so that generative AI engines mention, cite, and recommend you in their answers. It is the AI-era counterpart to SEO, aimed at the generated answer rather than the ranked link.

Why it matters

Generative engines increasingly sit between buyers and the open web, answering questions directly instead of returning ten links. If your brand is not part of what they generate, you lose demand upstream of your funnel. GEO is how you compete for that position, and like SEO it is a discipline, not a one-time fix.

How to measure it

You measure GEO by tracking the outcomes it targets: mention rate, recommendation rate, position, citation share, and competitive share of voice across each engine. Because GEO work pays off as model and source signals update, the right read is a trend over time tied to the specific changes you shipped.

Recommendation rate
Active endorsement by AI.
Citation share
Whether your sources are used.
Position
Where you land in answers.
Share of voice
Your slice versus rivals.

How Rankry helps

Rankry is the measurement and action layer for GEO: it shows what to fix and whether it worked.

  • Tracks every GEO outcome across five engines
  • Surfaces the prompt and source gaps to close next
  • Trends results so you can attribute GEO work to movement
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Related

FAQ

GEO questions

Is GEO the same as SEO?
They overlap but differ. SEO optimizes for ranked links on a results page; GEO optimizes for being mentioned and recommended inside a generated answer. Strong SEO helps GEO, especially on Google-grounded engines, but GEO adds concerns SEO does not cover.
How do I do GEO?
Be crawlable to AI bots, position your brand clearly, publish category and comparison pages, earn third-party corroboration, add structured data, and keep content current. Then measure the outcomes per engine and close the gaps.
How is GEO measured?
Through AI visibility metrics: recommendation rate, citation share, position, and share of voice, tracked per model and over time rather than as a single snapshot.