2026 GLP-1 Clinic AI Visibility Index
An open index of how ready GLP-1 and medical weight loss clinics are to be cited by AI engines, measured across 233 clinics in 28 US metros. The metro-by-metro readiness ranking, the signal gaps, and the open dataset behind it.
The GLP-1 Clinic AI Visibility Index measures how ready GLP-1 and medical weight loss clinics are to be cited by AI engines. We audited 233 clinic websites across 28 US metros (216 reachable) for the structural signals ChatGPT, Perplexity, Gemini, Claude, and Google AI need to verify and cite a local business. Only 21% are fully citation-ready. The dataset is open under CC BY 4.0.
The headline findings
- 21% are fully citation-ready (46 of 216 reachable clinics).
- 40% publish no LocalBusiness structured data (86 clinics) — the single most common gap.
- Only 10% use FAQ structured data, and 64% have no FAQ content at all (139 clinics).
- Only 37% publish an llms.txt manifest.
- 97% do not block AI crawlers. Access is not the problem. The absence of evidence once the crawler arrives is.
The metro readiness index
Every reachable clinic scored across 28 metros, ranked by the share that are fully citation-ready. Small per-metro samples mean the ranking is directional, not a league table; the consistent signal is that most clinics in every metro are not ready.
| Rank | Metro | Clinics audited | Citation-ready | Ready % |
|---|---|---|---|---|
| 1 | Indianapolis, IN | 8 | 4 | 50% |
| 2 | Raleigh, NC | 4 | 2 | 50% |
| 3 | Chicago, IL | 7 | 3 | 43% |
| 4 | Phoenix, AZ | 7 | 3 | 43% |
| 5 | Atlanta, GA | 8 | 3 | 38% |
| 6 | Scottsdale, AZ | 8 | 3 | 38% |
| 7 | Kansas City, MO | 9 | 3 | 33% |
| 8 | Austin, TX | 6 | 2 | 33% |
| 9 | Denver, CO | 7 | 2 | 29% |
| 10 | Las Vegas, NV | 7 | 2 | 29% |
| 11 | Dallas, TX | 8 | 2 | 25% |
| 12 | Miami, FL | 8 | 2 | 25% |
| 13 | Boston, MA | 9 | 2 | 22% |
| 14 | Seattle, WA | 10 | 2 | 20% |
| 15 | Charlotte, NC | 5 | 1 | 20% |
| 16 | Los Angeles, CA | 6 | 1 | 17% |
| 17 | Nashville, TN | 7 | 1 | 14% |
| 18 | San Diego, CA | 7 | 1 | 14% |
| 19 | Houston, TX | 8 | 1 | 13% |
| 20 | New York, NY | 8 | 1 | 13% |
| 21 | Orlando, FL | 8 | 1 | 13% |
| 22 | Philadelphia, PA | 8 | 1 | 13% |
| 23 | Minneapolis, MN | 9 | 1 | 11% |
| 24 | Tampa, FL | 9 | 1 | 11% |
| 25 | Washington, DC | 9 | 1 | 11% |
| 26 | Salt Lake City, UT | 9 | 0 | 0% |
| 27 | San Francisco, CA | 9 | 0 | 0% |
| 28 | Columbus, OH | 8 | 0 | 0% |
How the index is measured
The sample is GLP-1 and medical weight loss clinics surfaced by buyer-intent search across 28 tier-1 and tier-2 US metros. Each clinic's live homepage, robots.txt, and llms.txt were fetched (guarding against soft 404s), then scored for: a Schema.org graph, LocalBusiness/MedicalClinic structured data, FAQ structured data, any FAQ content, a served llms.txt, and whether AI crawlers are allowed. A clinic counts as citation-ready only when the structural evidence an engine needs is actually present. The full method and the reproducible harness are open; the complete writeup with row-level data is the AI Citation Readiness Gap report, and the data is downloadable as JSON under CC BY 4.0.
Why this is the leading indicator of AI citations
AI engines cite businesses whose facts they can read, verify, and quote. Readiness is the precondition: a clinic that publishes no structured data, no FAQ, and no clear pricing or eligibility gives the engine nothing to cite, so it names a competitor, a directory, or a telehealth brand instead. A 21% readiness rate means roughly four in five clinics are structurally invisible to AI search in their own market, regardless of how good their care is.
The demand side: which clinic each engine names
A second study measures the demand side directly — which specific clinic ChatGPT, Perplexity, Gemini, Claude, and Google AI actually name on a live buyer query. That requires querying each engine and recording the named businesses. That study is still in development, and we publish nothing from it until every engine adapter is verified and run. We do not estimate, model, or infer citation results. When the demand-side data is complete and verified, it will be added here as its own dataset. Until then, this index reports the readiness measurement we have actually collected.
How clinics can use the index
- See how ready clinics in your metro are, and how low the bar is to lead it.
- Map your own site against the five signals that decide readiness.
- Build the missing structured data, FAQ, and llms.txt before competitors do.
- Track your readiness over time as you close the gaps.
Get your city report
Want this run for your clinic's city against live buyer prompts now? The free 48 hour report applies the method to your metro and shows where you stand. Get your city report.
Related: the full Readiness Gap report · GLP-1 clinic AI search optimization · GLP-1 AI search prompt library · how we measure AI visibility.