A list of articles tagged “GEO”.
We expanded the machine-readability survey of 400 facilities in Osaka to the whole country, conducting a complete census of the machine readability of 7,643 aesthetic-related clinics. AI crawlers fully allowed 88.7%, llms.txt 9.1%, structured data 40.0%. And about one-tenth of registered URLs were unreachable.
We conducted a machine-readability survey of 400 facilities in Osaka Prefecture advertising cosmetic surgery, aesthetic dermatology, plastic surgery, or dermatology. AI crawlers fully allowed 89%, llms.txt present 10%, structured data 52%. The current state of medical institutions' "readiness."
Generative engine optimization (GEO) has research grounded in actual measurement. We organize the findings of two representative studies and consider how they can be translated into information delivery for medical institutions.
We ran a machine-readability survey of 67 domestic sites that explain AI search optimization. 93% allow all AI crawlers; 27% deploy llms.txt. The actual state of the "preparedness" on the explaining side, and a comparison with medical institutions.
Reflection in AI search does not necessarily stabilize right after publication. Rather than judging immediately after publishing, we organize when to observe and when to suspect a technical problem.
When patients ask an AI about medical institutions, how are clinics and doctors compared? This article organizes the information you want to have in order—across your website, doctor profiles, reviews, case examples, and FAQs—so that AI conveys your clinic's information correctly.
A primer on GEO and its relationship to LLMO and SEO. We explain the document design that helps medical institutions appear in the answers of generative AI.