Growing Call Center Revenue from $55M to $300M+ with AI, Savvy Marketing and Knowledge
For a Leading Nonprofit Academic Medical Center
“Turning a call centre into a patient acquisition engine requires knowing why people call, guiding agents to the right care, and connecting every conversation to an appointment.”
– A health leader seeking to turn calls into appointments and revenue.
When a leading medical center set out to transform its call center from a transfer point into a patient acquisition channel, an AI-enabled, knowledge-driven program delivered measurable business outcomes:
$55M to $300M+
Annual revenues attributed to the call center
30%
Increase in overall appointments
15%
Reduction in agent talk time
First call
Appointments scheduled and transactions closed during the initial call, replacing warm-transfer and triage-based handling
End-to-end
Tracking and revenue reconciliation from initial consult through surgery and discharge
Business Problem
A prospective patient picks up the phone, ready to book care. The agent can’t tell them which clinical area fits, can’t point to a physician with confidence, and transfers them to someone else. That was the daily reality at this medical center. Demand was growing, but the call center was a warm-transfer point, not a way in. There was no single source of physician information, so accurate referrals were out of reach, let alone appointments. Calls ran long, and access to care slipped further away.
Leadership couldn’t figure out why people were calling or which kinds of calls led to the volume. Marketing could show how money it spent, but not one single appointment that spending had created. The calls kept coming in. The patients weren’t being won over, and no one could explain why.
Customer Challenge
For a health system competing for patients, the first phone call is often the first impression, but the call center was not making the most of these interactions. Callers were often passed along instead of being connected to the right clinical area, physician, or appointment type, while long call durations delayed access to care.
Limited visibility, into the types of calls and how many calls came in also made it hard to plan for staff and training based on what was needed. Also, money spent on marketing could not be connected to appointments that were actually booked. This made it hard to see how well the marketing campaigns were working. The organization needed a scalable call center framework to improve call handling, verify insurance and payment options, route callers appropriately, convert calls into appointments on the first contact, and provide better visibility into call, revenue, and appointment data.
Movate Solution
Mova iO turned the call center from a place where calls were passed along into one where they become appointments. Agents now know why a patient is calling, which clinical area fits and how the patient will pay, so most appointments are booked before the call ends. Leadership can finally see what drives call volume and trace revenue back to the calls that produced it.
To get there, Mova iO implemented Salesforce service cloud to capture caller and patient details, including householding information, and used computer telephony integration (CTI) to automate lookups. A custom lightning web component guides agents through insurance verification, while knowledge and tailored user experience translate the caller’s reason into the right clinical area and appointment type. Salesforce and ACD data feed the enterprise data warehouse (EDW) to track revenue and appointments, and AI summarizes calls and surfaces insights about appointments.
Movate Applied AI Differentiator
Movate combined a CRM system, smart workflows and AI insight to turn a call center that used to hand off callers into an acquisition engine. Instead of checking each caller Movate now sets up appointments and finishes sales on the first call, supported by a top‑quality referral and appointment system that keeps service high.
What sets the approach apart is proof: a tracking and revenue reconciliation system follows each patient from initial consult through, when appropriate, surgery and discharge. Annual attributed revenue grew from $55 million to over $300 million; agent talk time fell 15% while appointments rose 30%, and non-clinician staff handled every interaction, creating a scalable model for sustained patient growth.
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