Appear client case study
Appear reports 3.6× AI-referred consultation interest for Dr. Gerstman.
Dr. Gerstman · Aesthetic medicine · New York City
Appear reports 3.6× AI-referred consultation interest after structuring treatment and physician information across 14 service and consultation pages.
Client results reported by Appear
Read the original studyPublished implementation timeline: weeks 1–12. This is TRC's summary of Appear's client work, not a TRC engagement or an independently verified result.
Source reviewed . Results vary by question, platform and measurement period.
AI-referred consultation interest, reported
Treatment and consultation pages structured
The Challenge
The New York aesthetic practice wanted AI answers to preserve its physician-led positioning, consultation approach and treatment-specific information rather than describe it as a generic med spa.
Appear describes connecting treatment categories, physician information and consultation context in machine-readable content.
Appear's approach
The published work covered entity mapping, service-page structuring and review of answers across multiple AI platforms.
Week 1
Map treatment and physician information
The practice's physician profile, treatment categories and consultation approach were organized into a structured model.
Weeks 2–4
Structure service pages
Fourteen treatment and consultation pages were prepared, including Botox, fillers, laser treatments, facials and brows.
Weeks 5–8
Monitor AI answers
Appear describes checking ChatGPT, Perplexity and Claude and refining pages where the positioning was not preserved.
Weeks 9–12
Review consultation interest
The source describes a review of AI-referred consultation growth and acquisition costs.
Work described in the study
Reported results
Appear reports a 3.6-times increase in AI-referred consultation interest and 14 structured service and consultation pages.
The publication describes consultation interest rather than disclosing confirmed booked appointments, completed treatments or revenue. This summary does not turn that interest measure into a sales claim.
Measurement context
- The original headline says 'AI-Referred Consults'; its explanatory text calls the measure 'consultation interest'. This summary uses the narrower description.
- The source does not disclose baseline consultation totals, attribution records or raw prompt counts. The 12-week implementation timeline is not an independently verified outcome window.
More case studies
HVAC & home services
Copeland Home Services
On the same 15 local HVAC questions, Appear recorded Copeland in 12 Gemini answers, up from five. The questions described a service need without supplying the company's name.
Read case studyLocal roofing
BYLTup
Appear reports a 73% ChatGPT mention rate and a 64% citation rate for the Long Beach roofer after eight weeks, alongside 18 published answer pages.
Read case studyPlan your next step in AI search.
Discuss your website, customer questions and priorities with TRC. We'll help define the work and how to measure it. Results are not guaranteed.
Book a free strategy call