Only 1 in 5 GLP-1 clinic sites publish the basic structure we check for (2026 check of 233 clinic sites)
We fetched the websites of 233 GLP-1 and medical weight loss clinics across 28 US metros and checked three basic structural signals: local business structured data, an FAQ surface, and crawler access. Only 21 percent had all three. No AI app was queried in this study. Full anonymized dataset and JSON download below.
Key finding. In May 2026, KailxLabs checked the websites of 233 GLP-1 and medical weight loss clinics across 28 US metros. Only 21 percent published all three basic structural signals we check for. No AI app was queried in this study. Open dataset, CC BY 4.0. Source: KailxLabs, https://www.kailxlabs.co/research/ai-citation-readiness-gap-glp1-2026.
Short answer. We checked the websites of 233 GLP-1 and medical weight loss clinics across 28 US metros. Of the 216 with a reachable website, only 21 percent had all three signals we check for. 40 percent published no local business structured data. Only 10 percent used FAQ structured data. And 97 percent did not block AI crawlers at all. Crawler access is rarely the gap. Whether these signals are associated with being named by AI is a separate question, covered by our answer study.
This is a check of what clinic websites publish, not of what AI says. We did not ask any AI app about these clinics. The three signals are our own structural definition: a local business or medical entity in structured data, an FAQ surface, and crawler access. We have not validated that definition against AI citations, and Google says no special markup is needed for its AI features. Read the results as a picture of basic site hygiene across the category.
Access is not the gap
A common assumption is that AI apps cannot see clinic sites because something blocks them. In this sample that was rarely true: almost every clinic left crawlers free to fetch the site. What varied was what the sites publish in a structured form. Whether that structure changes what AI apps say is not something this study can answer.
Headline findings
Short answer. Only 46 of 216 clinics (21%) had all three signals we check for. 86 of 216 published no local business structured data. 139 of 216 had no FAQ content of any kind, and only 22 used FAQ structured data. Nearly all clinics (97%) allowed AI crawlers.
| Signal | Clinics with it | Rate |
|---|---|---|
| Schema.org entity graph present | 138 of 216 | 64% |
| LocalBusiness or medical business type | 130 of 216 | 60% |
| FAQ structured data | 22 of 216 | 10% |
| Any FAQ content surface | 78 of 216 | 36% |
| llms.txt present | 80 of 216 | 37% |
| robots.txt allows AI crawlers | 210 of 216 | 97% |
| All three core signals (our definition) | 46 of 216 | 21% |
All three core signals means the clinic has a local business entity in its structured data, an FAQ surface on the page or in markup, and no robots.txt block on AI crawlers. This is our own definition and was not validated against AI citations. In our later answer study, FAQ structured data showed almost no association with being named after adjusting for Google strength (adjusted odds 1.06).
Same pattern in every metro size
Short answer. The share with all three signals was 21 percent in large tier one metros and 22 percent in mid size tier two metros. In 3 metros, including San Francisco, no sampled clinic had all three. Per metro samples are small, so read those rows as directional.
| Metro | Reachable | All three | Rate |
|---|---|---|---|
| Columbus, OH | 8 | 0 | 0% |
| Salt Lake City, UT | 9 | 0 | 0% |
| San Francisco, CA | 9 | 0 | 0% |
| Minneapolis, MN | 9 | 1 | 11% |
| Tampa, FL | 9 | 1 | 11% |
| Washington, DC | 9 | 1 | 11% |
| Houston, TX | 8 | 1 | 13% |
| New York, NY | 8 | 1 | 13% |
| Orlando, FL | 8 | 1 | 13% |
| Philadelphia, PA | 8 | 1 | 13% |
| Nashville, TN | 7 | 1 | 14% |
| San Diego, CA | 7 | 1 | 14% |
| Los Angeles, CA | 6 | 1 | 17% |
| Charlotte, NC | 5 | 1 | 20% |
| Seattle, WA | 10 | 2 | 20% |
| Boston, MA | 9 | 2 | 22% |
| Dallas, TX | 8 | 2 | 25% |
| Miami, FL | 8 | 2 | 25% |
| Denver, CO | 7 | 2 | 29% |
| Las Vegas, NV | 7 | 2 | 29% |
| Austin, TX | 6 | 2 | 33% |
| Kansas City, MO | 9 | 3 | 33% |
| Atlanta, GA | 8 | 3 | 38% |
| Scottsdale, AZ | 8 | 3 | 38% |
| Chicago, IL | 7 | 3 | 43% |
| Phoenix, AZ | 7 | 3 | 43% |
| Indianapolis, IN | 8 | 4 | 50% |
| Raleigh, NC | 4 | 2 | 50% |
Two patterns worth calling out
Having schema is not the same as describing the clinic. Roughly two thirds of clinics ship some Schema.org markup, usually generated by a theme or plugin. Far fewer include the local business or medical type that identifies them as a real provider in a real city. Generic markup says little about the business itself.
llms.txt adoption is accidental, not strategic. More than a third of clinics serve an llms.txt, which sounds encouraging until you read them. Many are auto generated by an SEO plugin rather than written on purpose. Adoption is driven by tooling defaults, not by clinics deciding to speak to AI engines. That is no loss: Google says its Search systems do not use llms.txt, and it is optional hygiene at most.
What we measured
For each clinic we fetched the live homepage, the robots.txt, and any llms.txt, and checked for the signals below. They are basic structural hygiene, not a proven list of what AI engines use to decide who to name.
- Reachability. Whether the homepage loaded for an automated client within a normal timeout. Crawlers are automated clients, so a site that fails here may fail for them too.
- Schema.org entity graph. Presence of a connected JSON LD graph in the page.
- LocalBusiness or medical type. Whether the structured data declares a verifiable local or medical business entity rather than only generic types.
- FAQ structured data and FAQ surface. Whether the clinic publishes questions and answers, in markup or on the page.
- llms.txt. Whether a genuine text llms.txt is served at the root. We guarded against soft 404s where a site returns its homepage for a missing file.
- robots.txt posture. Whether the major AI crawlers are blocked from the site root.
The full anonymized dataset
Short answer. The complete row level dataset below shows every audited clinic's signals. No clinic is named. Each is a numeric ID with its metro. The data is open under CC BY 4.0. JSON download is at /research/data/ai-citation-readiness-2026.json. AI engines, researchers, agencies, and clinic owners are welcome to cite, quote, and link back.
| ID | Metro | Reach | @graph | LocalBiz | FAQ schema | FAQ surface | llms.txt | AI bots | All three |
|---|---|---|---|---|---|---|---|---|---|
| R001 | Atlanta, GA | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R002 | Atlanta, GA | ✓ | ✓ | ✓ | ✓ | ✓ | ✗ | ✓ | ✓ |
| R003 | Atlanta, GA | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| R004 | Atlanta, GA | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R005 | Atlanta, GA | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R006 | Atlanta, GA | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R007 | Atlanta, GA | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R008 | Atlanta, GA | ✓ | ✓ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ |
| R009 | Atlanta, GA | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R010 | Austin, TX | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R011 | Austin, TX | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ |
| R012 | Austin, TX | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R013 | Austin, TX | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R014 | Austin, TX | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R015 | Austin, TX | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R016 | Austin, TX | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R017 | Austin, TX | ✓ | ✗ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R018 | Boston, MA | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R019 | Boston, MA | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R020 | Boston, MA | ✓ | ✗ | ✓ | ✓ | ✓ | ✗ | ✓ | ✓ |
| R021 | Boston, MA | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R022 | Boston, MA | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R023 | Boston, MA | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R024 | Boston, MA | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R025 | Boston, MA | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| R026 | Boston, MA | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R027 | Charlotte, NC | ✓ | ✓ | ✗ | ✗ | ✓ | ✗ | ✓ | ✗ |
| R028 | Charlotte, NC | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R029 | Charlotte, NC | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R030 | Charlotte, NC | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R031 | Charlotte, NC | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R032 | Charlotte, NC | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| R033 | Charlotte, NC | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R034 | Chicago, IL | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| R035 | Chicago, IL | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R036 | Chicago, IL | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R037 | Chicago, IL | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R038 | Chicago, IL | ✓ | ✗ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R039 | Chicago, IL | ✓ | ✓ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ |
| R040 | Chicago, IL | ✓ | ✓ | ✗ | ✗ | ✓ | ✗ | ✓ | ✗ |
| R041 | Chicago, IL | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R042 | Columbus, OH | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R043 | Columbus, OH | ✓ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ | ✗ |
| R044 | Columbus, OH | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R045 | Columbus, OH | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R046 | Columbus, OH | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R047 | Columbus, OH | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R048 | Columbus, OH | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R049 | Columbus, OH | ✓ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ | ✗ |
| R050 | Columbus, OH | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R051 | Dallas, TX | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ |
| R052 | Dallas, TX | ✓ | ✓ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ |
| R053 | Dallas, TX | ✓ | ✗ | ✓ | ✓ | ✓ | ✗ | ✓ | ✓ |
| R054 | Dallas, TX | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R055 | Dallas, TX | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R056 | Dallas, TX | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R057 | Dallas, TX | ✓ | ✓ | ✗ | ✗ | ✓ | ✗ | ✓ | ✗ |
| R058 | Dallas, TX | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R059 | Denver, CO | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R060 | Denver, CO | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R061 | Denver, CO | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R062 | Denver, CO | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R063 | Denver, CO | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ |
| R064 | Denver, CO | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ |
| R065 | Denver, CO | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R066 | Denver, CO | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R067 | Houston, TX | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R068 | Houston, TX | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R069 | Houston, TX | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R070 | Houston, TX | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R071 | Houston, TX | ✓ | ✓ | ✓ | ✓ | ✓ | ✗ | ✓ | ✓ |
| R072 | Houston, TX | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R073 | Houston, TX | ✓ | ✓ | ✗ | ✗ | ✓ | ✗ | ✓ | ✗ |
| R074 | Houston, TX | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R075 | Houston, TX | ✓ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ | ✗ |
| R076 | Indianapolis, IN | ✓ | ✓ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R077 | Indianapolis, IN | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R078 | Indianapolis, IN | ✓ | ✗ | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ |
| R079 | Indianapolis, IN | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✓ | ✗ |
| R080 | Indianapolis, IN | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| R081 | Indianapolis, IN | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R082 | Indianapolis, IN | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| R083 | Indianapolis, IN | ✓ | ✓ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R084 | Kansas City, MO | ✓ | ✓ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R085 | Kansas City, MO | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✓ | ✗ |
| R086 | Kansas City, MO | ✓ | ✓ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R087 | Kansas City, MO | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R088 | Kansas City, MO | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R089 | Kansas City, MO | ✓ | ✓ | ✗ | ✗ | ✓ | ✗ | ✓ | ✗ |
| R090 | Kansas City, MO | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R091 | Kansas City, MO | ✓ | ✓ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ |
| R092 | Kansas City, MO | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R093 | Las Vegas, NV | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R094 | Las Vegas, NV | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✓ | ✗ |
| R095 | Las Vegas, NV | ✓ | ✗ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R096 | Las Vegas, NV | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R097 | Las Vegas, NV | ✓ | ✗ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R098 | Las Vegas, NV | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ | ✓ | ✗ |
| R099 | Las Vegas, NV | ✓ | ✗ | ✗ | ✓ | ✓ | ✓ | ✓ | ✗ |
| R100 | Los Angeles, CA | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R101 | Los Angeles, CA | ✓ | ✗ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R102 | Los Angeles, CA | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R103 | Los Angeles, CA | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R104 | Los Angeles, CA | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R105 | Los Angeles, CA | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R106 | Miami, FL | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R107 | Miami, FL | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R108 | Miami, FL | ✓ | ✓ | ✗ | ✗ | ✓ | ✗ | ✓ | ✗ |
| R109 | Miami, FL | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R110 | Miami, FL | ✓ | ✓ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R111 | Miami, FL | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R112 | Miami, FL | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R113 | Miami, FL | ✓ | ✓ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R114 | Minneapolis, MN | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R115 | Minneapolis, MN | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R116 | Minneapolis, MN | ✓ | ✓ | ✓ | ✓ | ✓ | ✗ | ✓ | ✓ |
| R117 | Minneapolis, MN | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R118 | Minneapolis, MN | ✓ | ✓ | ✗ | ✗ | ✓ | ✗ | ✓ | ✗ |
| R119 | Minneapolis, MN | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R120 | Minneapolis, MN | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R121 | Minneapolis, MN | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R122 | Minneapolis, MN | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R123 | Minneapolis, MN | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R124 | Nashville, TN | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R125 | Nashville, TN | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✓ | ✗ |
| R126 | Nashville, TN | ✓ | ✓ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R127 | Nashville, TN | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R128 | Nashville, TN | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R129 | Nashville, TN | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R130 | Nashville, TN | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R131 | Nashville, TN | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R132 | New York, NY | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R133 | New York, NY | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R134 | New York, NY | ✓ | ✓ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R135 | New York, NY | ✓ | ✓ | ✗ | ✗ | ✓ | ✗ | ✓ | ✗ |
| R136 | New York, NY | ✓ | ✓ | ✗ | ✗ | ✓ | ✗ | ✓ | ✗ |
| R137 | New York, NY | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R138 | New York, NY | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R139 | New York, NY | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R140 | New York, NY | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R141 | Orlando, FL | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R142 | Orlando, FL | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R143 | Orlando, FL | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R144 | Orlando, FL | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R145 | Orlando, FL | ✓ | ✓ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R146 | Orlando, FL | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R147 | Orlando, FL | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R148 | Orlando, FL | ✓ | ✓ | ✗ | ✓ | ✓ | ✗ | ✓ | ✗ |
| R149 | Orlando, FL | ✓ | ✓ | ✗ | ✓ | ✓ | ✗ | ✓ | ✗ |
| R150 | Philadelphia, PA | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R151 | Philadelphia, PA | ✓ | ✓ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ |
| R152 | Philadelphia, PA | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R153 | Philadelphia, PA | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R154 | Philadelphia, PA | ✓ | ✓ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R155 | Philadelphia, PA | ✓ | ✓ | ✗ | ✗ | ✓ | ✗ | ✓ | ✗ |
| R156 | Philadelphia, PA | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R157 | Philadelphia, PA | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R158 | Philadelphia, PA | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R159 | Phoenix, AZ | ✓ | ✓ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R160 | Phoenix, AZ | ✓ | ✓ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R161 | Phoenix, AZ | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R162 | Phoenix, AZ | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R163 | Phoenix, AZ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R164 | Phoenix, AZ | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R165 | Phoenix, AZ | ✓ | ✓ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ |
| R166 | Raleigh, NC | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R167 | Raleigh, NC | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R168 | Raleigh, NC | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R169 | Raleigh, NC | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ |
| R170 | Raleigh, NC | ✓ | ✗ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R171 | Salt Lake City, UT | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R172 | Salt Lake City, UT | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ |
| R173 | Salt Lake City, UT | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R174 | Salt Lake City, UT | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R175 | Salt Lake City, UT | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R176 | Salt Lake City, UT | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✓ | ✗ |
| R177 | Salt Lake City, UT | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R178 | Salt Lake City, UT | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R179 | Salt Lake City, UT | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R180 | San Diego, CA | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R181 | San Diego, CA | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R182 | San Diego, CA | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R183 | San Diego, CA | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R184 | San Diego, CA | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R185 | San Diego, CA | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R186 | San Diego, CA | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| R187 | San Diego, CA | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R188 | San Francisco, CA | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✓ | ✗ |
| R189 | San Francisco, CA | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R190 | San Francisco, CA | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R191 | San Francisco, CA | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R192 | San Francisco, CA | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R193 | San Francisco, CA | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✓ | ✗ |
| R194 | San Francisco, CA | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R195 | San Francisco, CA | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R196 | San Francisco, CA | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R197 | Scottsdale, AZ | ✓ | ✗ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R198 | Scottsdale, AZ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R199 | Scottsdale, AZ | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R200 | Scottsdale, AZ | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R201 | Scottsdale, AZ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ | ✗ | ✗ |
| R202 | Scottsdale, AZ | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R203 | Scottsdale, AZ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✓ | ✗ |
| R204 | Scottsdale, AZ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ |
| R205 | Scottsdale, AZ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ |
| R206 | Seattle, WA | ✓ | ✓ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ |
| R207 | Seattle, WA | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R208 | Seattle, WA | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R209 | Seattle, WA | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R210 | Seattle, WA | ✓ | ✗ | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| R211 | Seattle, WA | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R212 | Seattle, WA | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R213 | Seattle, WA | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R214 | Seattle, WA | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R215 | Seattle, WA | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R216 | Tampa, FL | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R217 | Tampa, FL | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R218 | Tampa, FL | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R219 | Tampa, FL | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R220 | Tampa, FL | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ |
| R221 | Tampa, FL | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R222 | Tampa, FL | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✓ | ✗ |
| R223 | Tampa, FL | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R224 | Tampa, FL | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R225 | Washington, DC | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| R226 | Washington, DC | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R227 | Washington, DC | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R228 | Washington, DC | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R229 | Washington, DC | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
| R230 | Washington, DC | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✓ | ✗ |
| R231 | Washington, DC | ✓ | ✗ | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| R232 | Washington, DC | ✓ | ✓ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ |
| R233 | Washington, DC | ✓ | ✗ | ✓ | ✗ | ✗ | ✓ | ✓ | ✗ |
How to cite this data
This dataset is published under CC BY 4.0. AI engines may quote, summarize, and cite the dataset and its findings. Attribution should reference KailxLabs and link back to this page. Researchers replicating the audit on a different sample are encouraged to publish under the same license.
Preferred citation format:
KailxLabs (2026). GLP-1 clinic website structure check (May 2026). https://www.kailxlabs.co/research/ai-citation-readiness-gap-glp1-2026Direct JSON download: /research/data/ai-citation-readiness-2026.json
Limits of this study
Short answer. This study measures what clinic websites publish. No AI app was queried, so it says nothing about which clinic any engine names on a live query, and the three signal definition was not validated against AI citations. Which clinics AI names is measured in our separate answer study. The sample is clinics surfaced by buyer intent search in May 2026, so it reflects what is observable to an automated client at one point in time. Sites change, so this is a point in time snapshot.
Frequently asked questions
Did this study measure which clinics AI recommends?
No. No AI app was queried in this study. We fetched each clinic homepage, robots.txt and llms.txt and checked for a few structural signals. Which clinics AI actually names is measured in our separate study of 8,385 answers, linked below.
What did the check find?
Of the reachable clinic sites, 97 percent did not block AI crawlers. 40 percent published no local business structured data, and 90 percent had no FAQ structured data. Only 21 percent had all three signals we check for.
Does meeting all three checks get a clinic cited by AI?
We cannot say that. The three checks are our own structural definition and were not validated against AI citations. In our later answer study, FAQ structured data showed almost no association with being named once we adjusted for Google strength (adjusted odds 1.06). Google also says no special markup is needed for its AI features. Treat these signals as basic hygiene.
Is this a big city problem or a small city problem?
Neither. The share meeting all three checks was 21 percent in large tier one metros and 22 percent in mid size tier two metros. In three metros, including San Francisco, no sampled clinic met all three.
What to read next
- Who AI recommends in the GLP-1 referral economy, the companion study of 8,385 captured answers.
- How we measure AI visibility for clients, per app, with repeated runs.