How to get your med spa business recommended by AI.
Patients research injectables through AI before they ever book a consult. Be the clinic it names.
Are you in the AI answer in your city?
We test 10 realistic med spa customer queries across ChatGPT, Claude, Gemini, and Perplexity.
Customer Intent
Queries your customers ask AI assistants
These are typical high-intent questions asked to ChatGPT and Perplexity in the med spa space:
Signals & Algorithms
Key ranking factors for Med Spas & Aesthetic Clinics
Named Practitioners with Credentials
Aesthetic queries are trust queries. A named, credentialled injector on the page is what an engine repeats.
Device and Brand Specificity
Patients ask by brand — Botox, Dysport, Morpheus8, CoolSculpting. Sites that name devices match those questions; sites that say 'skin treatments' do not.
Safety and Consultation Content
Engines are conservative on medical topics and prefer sources that discuss suitability, risks and aftercare.
Optimization Roadmap
Action plan to win recommendations
Build a page per treatment brand
One page each for the named treatments you actually offer, with pricing ranges.
Publish provider credentials
Full name, qualification and training for each injector, in text rather than an image.
Add MedicalBusiness schema
JSON-LD with specialties, provider names and location.
Use Schema.org/MedicalBusiness
Structured data allows ChatGPT search and Perplexity crawlers to extract verified operating hours, phone numbers, and service areas in milliseconds without guesswork.
FAQ
Frequently asked questions
Why are AI engines cautious about recommending med spas?
Aesthetic medicine is a health topic, so engines weight demonstrable credentials and safety information heavily. Clinics that publish practitioner qualifications and honest risk information are named far more readily.
Do treatment prices need to be public?
Publishing ranges helps considerably. A large share of AI queries include cost, and a page that answers it is the one an engine can cite.