How a Multi-Practice Dental Group Recovered $47K in Revenue from Missed Calls
Executive Summary
A growing dental services organization (DSO) operating 26 practices sought to better understand and improve phone-based patient acquisition. Despite robust patient demand, leadership suspected that a meaningful number of inbound calls were going unanswered or failing to convert to booked appointments — costing the organization revenue and eroding the patient experience.
The group implemented Peerlogic, an AI-powered call intelligence platform, to gain full visibility into every patient call and automate follow-up for missed contacts.
About the Practice
For multi-practice dental groups, the phone remains the primary conversion channel — and small improvements in answer rates and caller handling translate directly into significant revenue gains. By deploying AI call intelligence, this organization moved from flying blind to having practice-level data on every call, every conversion opportunity, and every dollar at risk from unanswered contacts.
The $47,088 recovered in a single month from Aimee alone represents a compelling return, and the underlying conversion data provides a roadmap for continued improvement across all 26 practices.
The Challenge
Prior to deploying a call analytics solution, the organization faced three core problems:
- No visibility into how many calls were being missed or mishandled across practices.
- No standardized follow-up process for unanswered calls, meaning prospective patients frequently moved on to competing practices.
- No data to distinguish new patient conversion performance from existing patient scheduling activity — making it impossible to identify which practices or staff needed coaching.
A post-implementation analysis revealed that calls disconnecting prematurely were the single most common reason a caller did not book an appointment — a solvable operational problem once identified.
%201.svg)
The Solution
AI Call Intelligence & Automated Re-Engagement
The organization deployed Peerlogic across all 26 locations, enabling:
- Real-time AI transcription and analysis of every inbound and outbound call.
- Automated identification of captured leads that did not convert to scheduled appointments.
- Aimee, Peerlogic’s AI re-engagement assistant, which automatically followed up with patients who called but did not book.
- Practice-level and group-level dashboards surfacing conversion funnels, answer rates, and top reasons for non-conversion.
Results (Last 30 Days)
Call Performance
Across all 26 practices during the February 2026 measurement period:
- 62% average call answer rate — establishing a clear baseline and revealing that 38% of inbound calls were not being answered by front desk staff in real time.
- 40% overall average conversion rate across all patient types, with significant variance between new and existing patients.
- Calls disconnecting prematurely identified as the #1 reason patients did not book — a finding that directly informed staff training priorities.
The data revealed a substantial gap between new and existing patient conversion — 25% vs. 56% respectively. This directional insight surfaced a clear opportunity: with targeted front desk coaching and scripting improvements for new patient calls, the organization could significantly close that gap.
Aimee: Recovering Revenue from Missed Calls
Peerlogic’s AI re-engagement assistant, Aimee, operated as a 24/7 follow-up layer for calls that did not reach staff. During February 2026:
- 40% engagement rate — meaning 4 in 10 patients who missed a connection responded to Aimee’s automated outreach.
- 144 appointments booked directly through Aimee across all practices.
- $47,088 in estimated recovered revenue that would otherwise have been lost.
- 2% missed call conversion rate — a baseline that the organization is actively working to improve by expanding Aimee’s deployment and optimizing outreach timing.
Key Takeaways
01
Call intelligence revealed that premature disconnects — not scheduling complexity — were the primary conversion killer. This is a fast, low-cost problem to fix once it is visible.
02
New patient conversion (25%) lagged existing patient conversion (56%) by more than 30 points, highlighting a specific training and scripting opportunity for front desk staff handling first-time callers.
03
AI-powered re-engagement through Aimee recovered $47,088 in a single month from calls that previously would have resulted in no follow-up whatsoever.
04
With 38% of calls going unanswered, the organization now has a clear and quantified incentive to invest in call coverage — whether through staffing adjustments, overflow routing, or AI answering.
Conclusion
With Peerlogic, Grand Central Smiles turned their front desk into a proactive, revenue-generating team—improving patient experience and capturing growth opportunities without hiring additional staff.
Headline + Quote
.svg)
.svg)
.svg)
