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GEO · Fundamentals

What is generative engine optimization (GEO)?

Generative engine optimization is the practice of improving how often and how accurately AI assistants — ChatGPT, Perplexity, Gemini, Copilot, Google’s AI Mode and AI Overview — mention, cite and recommend your brand in their generated answers.

SEO asks: does my page rank? GEO asks: does the answer name me, and which of my pages did it read?

Why it’s a separate discipline

A search result page is a list; an AI answer is a composition. The engine reads many pages, picks a few to cite, and writes a single response. Three consequences follow:

What GEO work actually looks like

  1. Prompt sets, not keyword lists. Collect the natural-language questions your buyers ask (“best CRM for small agencies”), grouped by intent.
  2. Repeated measurement. Run the set on a schedule across engines and markets; answers drift, so one-off checks mislead.
  3. Source analysis. Read which pages get cited — they’re often Reddit threads, comparison posts and docs, not your homepage. Those are the pages to create or improve.
  4. Content for citability. Pages that state a clear claim with evidence get cited; vague marketing pages don’t.

Measuring it

The practical stack is an answer monitoring API: submit each prompt, get back the answer text, sources[], entities[] and searchQueries[], then compute mention rate and citation share per market. How to track what AI assistants say about your brand walks through the setup, and query fan-out explains the search layer underneath.

GEO doesn’t replace SEO — the fan-out searches still hit Google’s index. But the thing being optimized has changed shape: from a ranking to a citation inside a written answer.

Try it on your own prompts

500 free credits a month, no card. One POST returns the answer, sources and citations as JSON.

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