Traditional search
A list of links the patient must compare.
Medical AI Visibility
When patients ask AI for a clinic, does it recommend yours?
We measure your visibility across ChatGPT and other AI platforms, uncover why competitors are recommended more often, and help close the gap.
AI VISIBILITY / 01
Sample country-based hair transplant AI visibility benchmark
Sample design: 30 queries × 3 independent runs
Your clinic was not explicitly recommended in this sample answer.
A different shortlist
Ranking on Google does not mean appearing in an AI recommendation.
Search results offer pages to explore. AI answers often compress that research into a small set of named clinics. The commercial question is no longer only “Do we rank?” It is also “Do we make the shortlist?”
AI recommendation
A concise shortlist with named options and supporting sources.
The benchmark design
A repeatable sample, not a mystery score.
The scope is frozen before collection. The same query set is observed independently, then every answer is reviewed against explicit rules.
30market-, language-, and treatment-specific queries
×3independent observations for every query
=90dated observations in the sample design
30 × 3 = 90 is an illustrative benchmark design, not a claim about a completed client study.
Four outcomes, kept separate
Mentioned is not the same as recommended.
Mention
Was the clinic named in a successful answer?
Explicit recommendation
Was the clinic clearly recommended or ordered?
Top position
Did it appear in the defined leading positions?
Supporting source
Was a reviewed clinic-associated source cited?
Example forensic finding
The gap is rarely “more content.” It is usually more specific.
The benchmark connects lost queries to the entities, evidence, and external sources that appear around competitors but not around your clinic.
Explore the benchmark serviceIllustrative structure and sample data. No real clinic is represented.
Competitor Clinic A
- Physician-led evidence
- Procedure-specific pages
- Consistent external sources
Your clinic
- General service pages
- Weak clinician linkage
- Few corroborating sources
11 opportunity clusters
Example only: trust, aftercare, procedure choice, physician involvement, and UK patient questions.
From evidence to action
A clear four-step engagement.
Two linked engagements
The benchmark diagnoses the gap. Monthly implementation closes it.
Start with a defined baseline. Continue only where the evidence supports a focused implementation backlog.
AI Visibility Benchmark
Measures the current position, explains lost queries, and identifies the evidence, entity, and source gaps to address first.
Outcome: baseline, diagnosis, and prioritized roadmap.Monthly implementation
Turns the roadmap into governed work across expertise evidence, entity consistency, source authority, QA, and re-measurement.
Outcome: completed priorities and observable change over time.- 01
Benchmark
Freeze the market, language, query set, and competitor scope.
- 02
Diagnose
Separate mentions, recommendations, positions, sources, and lost queries.
- 03
Execute
Prioritise expertise evidence, entity consistency, and source authority.
- 04
Re-measure
Repeat a comparable benchmark to measure observable change.
Start with the evidence
Find out whether your clinic makes the AI shortlist.
Request a private benchmark scoped to your priority market, language, treatments, and competitors.
Request a Benchmark