What is GEO generative engine optimization
Generative Engine Optimization (GEO) is the practice of optimizing content so it gets surfaced and cited by generative AI models — ChatGPT, Claude, Gemini, Perplexity. It overlaps with AEO (which focuses on direct-answer citation) but covers the broader question of how AI models *encounter* your content in the first place. For most advisors the practical playbook is the same: structured answers, schema, authority, freshness.
SEO, AEO, GEO — the stack
- SEO = rank on classical search engines (Google, Bing).
- AEO = get cited when an AI engine answers a specific question.
- GEO = get found and used by generative AI models more broadly, including in research, summaries, and conversational answers.
They are layered, not competing. A page that wins at SEO usually wins at AEO and GEO too — the underlying signals overlap.
What's different about GEO
- It cares more about how content is structured than how it's keyword-targeted.
- Llms.txt files (a new standard for telling AI crawlers about your site) matter.
- Crawl budget matters — if AI crawlers hit your site once a week, frequent updates pay off.
- Citations to your site from authoritative sources weigh heavier in GEO than in classical SEO.
The practical takeaway for advisors
Don't get lost in the acronym soup. Publish direct, structured, citation-worthy answers on a real domain, mark them up with schema, link to authoritative sources, and update them. That single playbook wins SEO, AEO, and GEO at the same time.
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