GEO (Generative Engine Optimization) is the practice of structuring content so AI answer engines — ChatGPT, Claude, Gemini, Perplexity — cite it directly in their responses, rather than just ranking it in a list of blue links. It’s the successor discipline to traditional SEO, built for a world where people ask a chat window instead of a search box.
Why GEO is different from SEO
| Traditional SEO | GEO | |
|---|---|---|
| Success metric | Ranking position | Citation frequency |
| Content shape | Long pages optimized for scanning | Answer-first, direct claims an LLM can quote |
| Distribution | Search index | LLM training + retrieval + live browsing |
| Feedback loop | Weeks (crawl/rank cycles) | Continuous — re-queried every conversation |
What actually gets cited
Across the answers Source collects, three patterns show up again and again:
- Direct, quotable claims near the top of the page — not buried after three paragraphs of preamble
- Tables and lists over dense prose, because they’re easier for a model to lift verbatim
- Content that names the comparison explicitly (e.g. “X vs. Y”) when the query has switching intent
That’s the brief Solve writes every draft against — grounded in the same GEO research this post summarizes, kept current as the underlying platforms change how they cite sources.
How to know if it’s working
You need a way to see, per platform, whether you’re actually showing up — that’s what Operate is for: brand visibility percentage, citation share, and a competitor ranking table, refreshed every time Source runs.