AEO and AI visibility

Patients stopped scrolling. They started asking.

A patient who needs a GP used to open Google, get ten links, and pick one. Increasingly they open ChatGPT and ask a question in plain language. What comes back is not a page of options. It is two or three practices, named, with a reason attached to each.

That is a much smaller list to be on, and the practices already on it are not there by accident.

How an engine decides who to name

Large language models do not rank pages the way a search engine does. They assemble an answer from sources they can read, verify and trust. In practice that means a handful of things decide whether your practice is in the answer.

Whether a model can read your site at all. Whether your services, locations and practitioners are published in a form it can parse rather than infer. Whether what you say about yourself matches what directories, your Google Business Profile and review platforms say about you. And whether anyone has written a clear, direct answer to the question the patient asked.

Most practices fail on all four, and none of the failures are visible from the front end. The site looks fine. The traffic looks fine. The practice is simply not in the answer.

What we actually do

We make your practice legible to machines without making it worse for people.

That means publishing your structure properly, so an engine knows that you are a general practice in a named suburb with six practitioners, specific services and specific hours, rather than guessing from body copy. It means making your listings agree with each other. It means writing the answers to the questions your patients type, in the format a model will quote.

Then we measure it, every month, against where you started.