AI for Aesthetic Medicine Centers: Over 100 Appointments from Warm Leads
Over 100 doctor appointments booked by AI over the phone.
# AI for Aesthetic Medicine Centers: Over 100 Appointments from Warm Leads In an aesthetic medicine center, contact lists grow faster than the time available to call them back. Those who inquired, those who visited once, those who showed interest but didn't book: these are people already familiar with the center, but no one has the hours to call everyone. In this case study, we explain how a network of aesthetic medical centers entrusted this work to a voice agent built on DeepAgent. In six weeks: 4,872 calls, 1,409 conversations, and **108 appointments booked with doctors**, with 26 hours spent on the phone by the agent, not staff. This is a concrete example of **AI for aesthetic medicine centers** applied to telephone outreach. ## The Client: A Network of Aesthetic Medical Centers ### Who they are The client is a network of aesthetic medicine centers in Italy. Doctors' schedules need to be filled every week, and a significant part of the commercial effort involves the phone: calling back those who have already made contact and bringing them back to the center. ### The starting point They had archives of "warm" contacts: people who already knew the center but hadn't yet taken the next step. Calling them manually means hours taken away from staff who care for patients. A method was needed to call everyone consistently, without disrupting the centers, and convert those lists into scheduled visits. ## The Challenge: Reaching Thousands of Contacts Without Disrupting Centers There were three difficulties, and the data confirmed them all. - **Many numbers, little time.** Lists of thousands of contacts, to be worked through while staff are busy with patients. - **Hard-to-reach contacts.** Answering machines, busy lines, switched-off phones: you have to find someone before you can speak. - **Few seconds to capture attention.** Someone answering an unknown number quickly decides whether to stay on the phone. ## How AI Works for Aesthetic Medicine Centers This project uses an **outbound voice agent**: an AI agent that calls the center's lists and manages the conversation from start to finish. **1. Calls the lists.** Thousands of numbers, without engaging staff. **2. Opens the conversation.** Introduces itself on behalf of the center and explains the reason for the call. **3. Qualifies.** Asks the right questions, one at a time, and handles objections. **4. Books the appointment and records.** Proposes a doctor's visit and saves the outcome of each call: appointment, conversation, voicemail, no answer, busy, unreachable number. Every attempt generates data, and this data shows where to intervene to book even more appointments. ## The Results: Six Weeks of Calls | Indicator | Result | |---|---| | Calls Made | 4,872 | | Conversations | **1,409 · 28.9%** | | Doctor Appointments Booked | **108 · 7.7% of conversations** | | Conversation Time | **26 hours** (1,556 minutes) | | Attempts without Conversation | 3,463 · 71.1% | The scope is from August 1st to September 11th. We excluded the initial calls from July, which should be considered tests. The appointments are doctor's visits booked by the agent during the call. The most important result is on the schedule: 108 appointments with doctors, one for every 13 conversations, generated from lists that would otherwise have remained dormant. And they were achieved without taking an hour away from staff: the agent conducted all 1,409 conversations, totaling 26 hours of phone time. ## The Data That Boosts Results: 7 Out of 10 Calls Don't Reach a Person If 1 in 13 conversations turns into an appointment, every additional person reached is valuable. The **outbound call contact rate** is therefore the main leverage. Out of 4,872 attempts: - **1,305** ended in voicemail (26.8%); - **795** rang without answer (16.3%); - **712** found a busy line (14.6%); - **591** found the number unreachable (12.1%). More than seven out of ten attempts stop before a conversation. For those looking to **re-engage warm leads**, the biggest margin for improvement isn't in the script but in reachability: different time slots, number of attempts per contact, callback rules after a voicemail or a busy signal. The second leverage lies in the first few seconds. Two out of three conversations end in less than 30 seconds; one in four lasts from 30 seconds to 2 minutes, and one in twenty exceeds 2 minutes. Those who stay on the phone are those who got past the opening: that's where appointments are built. ## What This Case Teaches and Where to Grow Further The result is clear: warm leads, consistently worked, lead to scheduled visits. Priorities for the next phase: - **More contacts reached.** Tests on time slots, number of attempts, and callback rules: this is where 71% of attempts are lost. - **A stronger opening.** Rewriting the first 30 seconds based on conversations that led to an appointment, providing the best sample of openings, questions, and proposals. - **Separate test data.** Keeping test calls out of the numbers, as we did with July. - **Support WhatsApp.** A message before the call, or after a missed call. The flow is designed but not yet active: it will only be measured once it's in production with an approved number, templates, and a published agent. ## The Agent Handles Calls, Doctors Fill the Schedule The value of **AI for aesthetic medicine centers** is seen in two numbers: 108 doctor appointments in six weeks and 26 hours of phone time saved for staff. And there's still room for improvement: reaching more contacts and retaining them in the first 30 seconds means more visits on the schedule with the same lists. **Discover our fleet of agents.** Each DeepAgent is designed to excel in its specific domain, and various companies are already using them to optimize their processes. **Leave your contact details and run a real-time test. Request a FREE demo and try our AI Agent. You will be called back immediately from the number: +39 06 8345191** Talk to sales → · Create your agent →