Case Study: 40% Fewer No-Shows with AI Appointment Reminders

No-shows are the silent revenue drain of every healthcare provider. A missed appointment means a blocked slot, a wasted doctor's time, and lost revenue that can never be recovered. For a 10-doctor clinic running 80 appointments per day, a 25% no-show rate translates to ₹4–6 lakh in lost monthly revenue.

The Client

A multi-specialty clinic chain with 8 branches in Bangalore was experiencing a 28% no-show rate despite having a WhatsApp reminder workflow. The problem was that WhatsApp messages were being ignored — patients saw them but didn't take action to confirm or cancel. The clinic needed two-way confirmation, not one-way broadcasting.

The Implementation

Alphoris was configured to call every patient 24 hours and 2 hours before their appointment. The AI agent would confirm the appointment and log the response. Patients who confirmed were removed from the list. Patients who cancelled triggered an immediate slot-fill workflow.

Month 1 Results

No-show rate dropped from 28% to 19% — a 32% improvement in the first month. The clinic used the freed slots to accommodate walk-ins and same-day bookings, recovering an estimated ₹2.1 lakh in revenue that would otherwise have been lost.

Month 3 Results

After refining the call script and timing (moving the reminder from 24 hours to 36 hours ahead), the no-show rate stabilised at 16.5% — a 41% reduction from the baseline. The AI was handling 650 confirmation calls per day across all branches. The clinic estimated net revenue recovery of ₹5.2 lakh/month against a cost of ₹18,000/month in Alphoris credits — an ROI of 28x.

Lessons Learned

• Voice confirmation outperforms text reminder by 3x for healthcare.
• Calling 36 hours ahead gives patients enough time to cancel and allows the clinic to fill the slot.
• A "did you need to reschedule?" prompt at the end of confirmation calls recovers an additional 8% of would-have-been no-shows.
• Data from AI calls (cancellation reasons) helped the clinic identify that 40% of cancellations were due to transport issues — prompting them to partner with a local cab aggregator.