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Generative Engine Optimisation (GEO)
Generative Engine Optimisation is the practice of structuring a page so AI answer engines, ChatGPT, Perplexity, Google AI Overviews, can extract and cite it directly. It differs from traditional SEO by prioritizing self-contained, answer-shaped passages over keyword density and backlink volume.
How is GEO different from traditional SEO?
| Traditional SEO | GEO |
|---|---|
| Optimises for a ranking algorithm returning a list of links | Optimises for a model that extracts one passage and synthesizes an answer |
| Unit of optimisation: the page | Unit of optimisation: the paragraph |
| Backlink volume and keyword density matter | Self-contained facts and low hedging matter more |
Does an llms.txt file help with GEO?
Marginally, and not for the reason most vendors claim. Google’s Gary Illyes stated on the record in July 2025 that Google does not support llms.txt and has no plans to, and independent monitoring of AI bot traffic found answer-engine crawlers largely ignore the file and crawl HTML directly. Static rendering, answer-first structure and schema markup carry far more weight.
What actually moves AI citation rates?
Documented factors include source authority, structured-data parseability (schema.org markup), question-answer concision, and cross-source consensus on a claim. Brand search volume also correlates with AI citation more strongly than most on-page factors, off-site entity presence does work the page itself cannot.