Building the Reputation Program

The Problem

Before implementing this program, U.S. Dermatology Partners had no real reputation management process. Reviews were handled office by office, case by case, with no system tying it all together. With the company in a high-growth phase and adding locations quickly, that approach became unsustainable; there was no way to see how the organization was actually doing across dozens of practices at once.

The CMO decided to formalize a reputation management program and chose BirdEye as the platform. I was assigned as program manager and administrator. The assignment made sense on a few fronts: reviews were already appearing on the social media channels I governed; I had prior experience helping medical practices manage their reputations from my time at TNT Dental, and writing clear, appropriate review responses was squarely in my skill set.

The stakes went beyond reputation for its own sake. Google factors review volume, recency, and rating into how local business listings rank in search results, so for a company opening new locations quickly, a strong review profile wasn't just good PR; it directly affected how easily a new or existing patient could find a practice in search results in the first place.

The Solution

I built and administered a program with two halves: getting reviews in the door, and managing what happened once they came in.

Setting Up the Platform

BirdEye served a dual purpose. After an appointment, patients received an automated email requesting a review. Once reviews came in, the platform let us collect, monitor, and respond to them, and report on office performance at the regional, state, and individual office levels. At full scale, the program covered 260+ providers and 800+ review profiles, since each office and each individual provider could have individual profiles across multiple platforms, Google Business Profiles, Healthgrades, Facebook, Yelp, and Doctors.com among them, all monitored through the same system.

Onboarding a New Office

Bringing a new location into the program had several steps. Our backend team connected the office's appointment and patient system to BirdEye via an API, so the platform could see appointments and trigger review requests automatically. Each office's location and provider listings across every review platform had to be checked and optimized. Users, typically the office manager or administrator, though sometimes the provider themselves, were then added to BirdEye. Every new user was required to attend a monthly training session I hosted before working independently in the system.

Response Strategy: Automation Where It Helped, Judgment Where It Mattered

For positive reviews above a set star threshold, BirdEye automatically posted a response from a rotating set of thank-you messages I wrote, so replies went out quickly without ever reading as an obvious auto-response. Negative reviews were a different matter and stayed in human hands: office-level BirdEye users were responsible for responding, and I served as their go-to resource on the toughest ones.

Governance mattered here too. BirdEye could flag reviews containing language that suggested a possible HIPAA or privacy concern. When that happened, we routed the review to our compliance team for recommendations on how to respond rather than leaving an office manager to handle it alone, an important safeguard given how much sensitive information can show up in a healthcare review.

Monthly Training

I hosted a monthly training for every new BirdEye user, covering platform mechanics first (logging in, viewing reviews, responding, pulling reports) and then moving into response strategy and best practices, including directions to reach out to me for guidance with difficult negative reviews. After an initial wave of onboarding when the program first launched, new users came on at a steady pace of about three to five a month, tied to new office openings, and that cadence held steady across the roughly seven years I ran it.

Results

Review volume grew meaningfully once we were actively requesting reviews from patients, something that simply wasn't happening before the program existed, and response times improved because reviews were now being actively monitored instead of discovered by chance. Leadership and providers responded well to the program, largely because it gave them visibility they hadn't had before; it's hard to fix problems that you don't know exist. Google star ratings and NPS scores both improved under the program. During my time managing the program, U.S. Dermatology Partners averaged a 4.8 to 4.9-star rating on Google company-wide, with NPS scores in the 80 to 85 range across offices, a strong result on a scale that runs from -100 to +100.