Intelligence
Mapped patient questions, competing clinics, recurring AI recommendations, influential sources and the day-one Shareof.ai baseline.
We began working with The Treatment Rooms London in May 2026. The clinic already had an unusually strong clinical story: surgeon-led care, a large library of patient outcomes and meaningful third-party authority. Our opportunity was to turn those scattered strengths into a connected acquisition system that search engines and AI answer engines could retrieve, understand and corroborate.
Instead of chasing one broad “hair transplant London” ranking, we organized the market around the decisions that precede a consultation: clinic selection, technique, candidacy, cost, discretion, recovery, safety and proof. We then measured the brand across a 20-answer buyer-intent sample and connected the visibility work to referral outcomes reported by the clinic.
The clinic reported a 25% increase in referrals attributed to ChatGPT and Claude from June onward. That is the result that matters: not simply appearing more often, but becoming part of how prospective patients discover and shortlist the clinic.
25% growthClinic-reported referral volume, indexed to the June baseline.
Referral result supplied by The Treatment Rooms London. Indexed values illustrate the reported 25% increase and do not disclose the clinic’s private patient counts.
Shareof.ai sampled 20 answers across buyer questions covering clinic selection, procedures, cost, proof and surgeon evaluation. We paired that answer-level evidence with DataForSEO search coverage and live source checks to see which owned pages could support each decision.
The 20-answer sample is a point-in-time market measurement. Search positions and AI answers can vary by location, model and date. Shareof.ai keeps search coverage, answer visibility and referred business outcomes as separate evidence layers.
The work runs as one operating cycle, with each deliverable connected to a commercially valuable patient decision.
Mapped patient questions, competing clinics, recurring AI recommendations, influential sources and the day-one Shareof.ai baseline.
Scored opportunities by consultation value, designed the page backlog and defined the evidence, source and internal-link requirements.
Strengthened priority service, cost, comparison and education surfaces, then added technical structure and the first authority work.
Expanded early winners, closed corroboration gaps and measured prompt, citation and search movement against the May baseline.
We inspect the actual prompts, recommendations, competitors and citations instead of reducing AI visibility to a single score.
DataForSEO ranking and demand data shows where intent already exists and which owned page should compete for it.
We identify the publishers, directories and third-party pages that repeatedly shape both search results and AI answers.
The output is not another audit. Research becomes pages, technical changes, evidence, internal links and authority initiatives.