Review Generation and Reputation Recovery for a Family Dental Group
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Overview
What we built
A 26-location family dental group was stuck at 3.6 stars on Google, with hundreds of reviews sitting unanswered. We built the programme that let its happiest patients finally be heard.
In plain terms: the group's online reputation had drifted a long way from the care being delivered in its practices. Happy patients finished their visits and were never asked to share the experience, so the unhappy few dominated every profile. Several hundred reviews sat unanswered, some for over two years, and front-desk teams had neither the time nor the tools to respond. At the lowest-rated offices the damage was measurable: new-patient calls were noticeably weaker, because a star rating is the first thing a prospective patient checks.
We connected review requests to the moment that matters: the visit itself. An automated programme now sends a post-visit SMS invitation from each practice, routes every new review to the right office, and gives teams approved templates and escalation paths for responding. We also cleared the historical backlog office by office. Within 12 months the group's average Google rating rose from 3.6 to 4.4 stars, new reviews grew from roughly 35 to 290 a month, and 96% of incoming reviews are now answered within 48 hours. First-wave offices booked 11% more new patients than locations still waiting for rollout.
The Problem
3.6 stars and unanswered reviews
The group's 26 practices were busy and, by most accounts, well liked. The reviews said otherwise. Google profiles averaged 3.6 stars, and the gap between the care delivered and the reputation displayed widened every month, because feedback only arrived when someone was upset. A satisfied patient had no prompt, no link and no reason to write anything, while a frustrated one needed no encouragement at all.
The silence on the group's side made it worse. Several hundred reviews sat unanswered, some for over two years, which read to prospective patients as indifference. Front-desk teams were not ignoring the problem by choice: they had no time between check-ins, no tooling to track what had been posted, and no guidance on what they were allowed to say to a clinical complaint in public.
The commercial signal was already visible. New-patient call volume was noticeably weaker at the lowest-rated offices, the places that most needed the pipeline. Regional managers could sense the pattern but had no way to compare locations, so reputation stayed an anecdote rather than a managed number, and each office was left to interpret its own profile alone.
No prompt for praise
Satisfied patients left the practice and moved on with their day. With no invitation to share feedback, the review stream skewed heavily towards the unhappy minority.
Years of silence
Several hundred reviews sat unanswered, some for over two years. To anyone researching a dentist, the silence read as a group that did not care.
No tooling or guidance
Front-desk teams had no console, no templates and no policy for public replies, so even willing responders left clinical complaints untouched rather than risk saying the wrong thing.
Weak new-patient pipeline
Call volume was noticeably weaker at the lowest-rated offices, and with no comparative view across locations, managers could not see where reputation was costing bookings most.
What it was costing them
Every star mattered at the front door: prospective patients checking a 3.6-star profile against a competitor's rarely called to give the practice a chance. The lowest-rated offices carried noticeably weaker new-patient call volume, marketing spend worked against the drag of the rating it landed on, and hundreds of unanswered reviews compounded quietly, telling every reader that feedback here goes nowhere.
The Solution
Automated review invitation programme
We built the programme around the group's own practice-management system, so asking for feedback became a by-product of running the day rather than another task for the front desk. When a visit completes, the system triggers an SMS invitation to the patient, routed to the correct office profile out of 26, and timed while the experience is still fresh.
For the team side we built a response console: every new review lands in one queue, approved reply templates cover the common cases, and clinical complaints follow a defined escalation path instead of being answered ad hoc in public. Alerts fire on every new low rating so a poor experience is met with a prompt, considered response rather than discovered weeks later. In parallel, we worked through the historical backlog office by office until nothing was left unanswered.
Finally we gave regional managers the comparative view they never had: a dashboard covering all 26 locations, showing ratings, review volume, response times and invitation performance side by side, so reputation is managed like any other operational number. Underperforming offices are now visible early, and the playbook that lifted the first wave travels with the rollout.
Key decisions
Invite at the moment of care
Review invitations trigger from the practice-management system after each visit, reaching patients while the experience is fresh instead of relying on staff to remember to ask.
Route reviews to the right office
Per-location routing sends each invitation and each incoming review to the correct one of 26 profiles, keeping accountability local rather than pooled at head office.
Templates with an escalation path
Approved reply templates handle routine feedback quickly, while clinical complaints escalate to the right people rather than being debated publicly by front-desk staff.
Clear the backlog first
We answered the historical backlog office by office before scaling invitations, so new visitors saw a profile that engages with feedback, not one still ignoring it.
One dashboard across locations
Regional managers track ratings, response times and review volume for all 26 locations in one place, turning reputation into a managed weekly number.
Measurable Impact
What changed after launch
Within 12 months the group's average Google rating rose from 3.6 to 4.4 stars across all 26 locations. New reviews grew from roughly 35 to 290 a month, driven by the automated post-visit invitations, and the balance of voices shifted: profiles now reflect the typical visit rather than the worst one. 96% of incoming reviews are answered within 48 hours, replacing a backlog that had exceeded 700 unanswered reviews.
The commercial effect showed where it matters. Over two quarters, first-wave rollout offices booked 11% more new patients than locations yet to launch, a like-for-like comparison the group could act on. Reputation is no longer a slow drift the practices watch helplessly: it is an instrumented programme with owners, response targets and a dashboard that regional managers review as routinely as production numbers.
Google rating
Averaging 3.6 stars across the group
4.4 stars across all 26 locations within 12 months
Review volume
Roughly 35 new reviews a month, skewed unhappy
290 a month via automated post-visit invitations
Response handling
700+ unanswered reviews, some over two years old
96% of reviews answered within 48 hours
New-patient bookings
Noticeably weaker calls at the lowest-rated offices
First-wave offices booked 11% more new patients over two quarters
Headline results
Average Google rating rose from 3.6 to 4.4 stars across all 26 locations within 12 months
New reviews grew from roughly 35 to 290 a month via automated post-visit SMS invitations
96% of incoming reviews now answered within 48 hours, down from a backlog of 700+ unanswered
First-wave rollout offices booked 11% more new patients than yet-to-launch locations over two quarters
Tech & Tools Used
What powered the build
Every tool below earned its place in this engagement. Here is the part each one played.
Node.js
Runs the backend services behind the programme, from visit-triggered invitation logic to review ingestion, low-rating alerts and the escalation workflow.
Twilio SMS
Delivers the post-visit review invitations by text, the channel patients actually open, with each message sent on behalf of the correct location.
SendGrid
Handles the programme's email notifications, sending low-rating alerts and escalation notices to practice teams and regional managers the moment they are needed.
Google Business Profile API
Pulls every new review into the response console per location and publishes approved replies back to the right profile without anyone logging into Google.
Open Dental API
The integration point with the group's practice-management system: completed visits trigger the invitation flow, so requests go only to patients who were actually seen.
PostgreSQL
Stores the programme's system of record: invitation state, review history, response status and per-location performance across every office.
Redis
Backs the queues that pace invitation sends and deduplicate alerts, keeping message volume orderly across a multi-location rollout.
Next.js
Powers the response console and the manager-facing screens where teams answer reviews, work escalations and watch their own location's numbers.
Metabase
Serves the regional dashboard comparing ratings, response times and review volume across every location for weekly management review.
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