CASE 1
Plastic Surgery Clinic
From missed enquiries to a controlled booking flow (AI reception + booking + reminders)
The clinic was receiving a steady stream of enquiries, but results were unstable:
- Calls were missed during peak hours.
- WhatsApp replies were delayed.
- Reception spent hours repeating the same answers (prices, availability, preparation).
- No-shows created gaps in the schedule.
Objective
Increase booked appointments, reduce no-shows, and reduce reception workload — with full visibility for management.
What we identified in the first Bottleneck Check
The bottleneck wasn't demand. It was process control across three points:
- Response speed (patients cool down quickly)
- Qualification (too much time spent on low-intent chats)
- Confirmation & reminders (preventable no-shows)
What we implemented:
1) AI Receptionist (WhatsApp + Website)
- Instant answers to FAQs (services, price ranges, timing, preparation)
- Qualification: collects booking-ready details
- Handoff to human only when intent is high (with a clean summary)
2) Booking + No-Show Control
- Booking flow: request → slot suggestion → confirmation
- Automated reminders (24h + 3h)
- Optional deposit/card hold for high-no-show procedures (when applicable)
3) Management Control Layer
- One pipeline: New → Qualified → Offered → Booked → Completed/Lost (with reason)
- Weekly conversion-by-stage view
Before working with us
- Median first response time2h 10m
- Missed call loss (no capture)12%
- Booking conversion from enquiries19%
- No-show rate17%
- Reception repetitive Q&A3.2h/day
- Calendar fill64%
After
- Median first response timeunder 2 minutes (24/7)
- Missed calls recovered into WhatsApp flow90%
- Booking conversion from enquiries31%
- No-show rate9%
- Reception repetitive Q&A1.1h/day
- Calendar fill82%