Guide · GEO/AEO
What is GEO/AEO for Hospitals? Measuring AI-Search Visibility
Patients now ask ChatGPT, Claude, Gemini and Perplexity to recommend clinics. GEO/AEO is about whether AI names you in its answer. Here is how it differs from SEO and why measurement comes first.
The shift: from search box to AI answer
More patients now ask a generative engine — “Which clinic is good for implants in Gangnam?” — and read a single synthesized answer that names only a handful of clinics. If your clinic is not among those named, you are effectively invisible, no matter how well you rank in a traditional search list.
GEO/AEO vs traditional SEO
SEO optimizes for a ranked list. GEO (Generative Engine Optimization) and AEO (Answer Engine Optimization) optimize for being named and cited inside the answer itself. Engines also differ: ChatGPT and Perplexity lean on Bing’s index, Gemini on Google’s, so the same clinic can appear in one engine and not another. That is why a neutral, multi-engine view matters.
Why measurement comes first
AI answers vary from run to run. A one-off check is noise; a fixed question set measured every two weeks is a trend. Boily measures your exposure rate, share of voice against competitors, and how it moves over time — across ChatGPT, Claude, Gemini and Perplexity. Improvement, if any, is framed as data-based clues, never a guarantee.
FAQ
What does GEO/AEO stand for?
GEO = Generative Engine Optimization; AEO = Answer Engine Optimization. Both describe being visible inside the synthesized answers of generative AI engines, rather than in a ranked list of links.
Is GEO the same as SEO?
They overlap (crawlable, well-structured, authoritative content helps both) but differ in the target. SEO aims for a position in a list of ten blue links; GEO/AEO aims to be one of the 2–5 sources an AI engine actually names in its answer. Different engines also ground on different sources (ChatGPT/Perplexity lean on Bing, Gemini on Google).
Can you guarantee my clinic will be recommended?
No one can credibly guarantee that, and for medical (YMYL) topics it is especially unreliable. Boily measures your current visibility neutrally; improvement is offered only as data-based clues, never a guarantee.
Why measure before trying to improve?
Without a baseline you cannot tell whether anything you change actually moved AI visibility. A frozen question set measured on a fixed cadence turns guesswork into a before/after you can trust.