CASE STUDY

AI Receptionist for Multi-Location SMB

How we deployed voice AI across 12 salon locations in under 2 weeks

The Challenge

A growing salon chain with 12 locations was losing 40% of incoming calls during peak hours. Their human receptionists were overwhelmed, leading to missed bookings and frustrated customers. They needed a solution that could handle appointment scheduling, answer common questions, and integrate with their existing Square Appointments system.

The Solution

Voice AI Implementation

  • • Custom voice agent trained on salon-specific terminology
  • • Natural conversation flow for appointment booking
  • • Integration with Square Appointments API
  • • Multilingual support (English, Spanish, Mandarin)

Technical Architecture

  • • Twilio for telephony infrastructure
  • • GPT-4 for conversation management
  • • ElevenLabs for natural voice synthesis
  • • Custom middleware for Square integration

Implementation Timeline

Days 1-3
Requirements gathering and system design
Days 4-7
Voice agent development and Square API integration
Days 8-10
Testing with real salon scenarios
Days 11-12
Pilot deployment to 2 locations
Days 13-14
Full rollout to all 12 locations

Results

60%
Reduction in handle time
35%
Increase in lead capture
98%
Call answer rate

The AI receptionist now handles 70% of all incoming calls without human intervention, books appointments directly into the Square system, and has increased overall booking conversion by 35%. The system paid for itself within the first month through increased bookings alone.

Client Testimonial

“The AI receptionist has transformed our operations. We're no longer losing customers to busy signals, and our human staff can focus on in-person service. The implementation was incredibly fast - we went from concept to all locations live in under two weeks.”
— Sarah Chen, Operations Director

Key Learnings

  • Voice AI can handle complex scheduling scenarios with proper training
  • Integration with existing systems (Square) is crucial for adoption
  • Gradual rollout (pilot → full deployment) reduces risk
  • Multilingual support significantly expands customer reach
  • Real-time monitoring and adjustment improves performance quickly

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