Maple AI Consultants

AI consulting case studies by Joel & Nanz Inc.

Moving Services • 18 Trucks

Case Study 32: Moving Company

Marketing-optimized case study for Canadian SMBs.

$104,000
Annual Savings
430%
ROI
3.0 months
Payback
Moving Services • 18 Trucks
Industry Focus

Executive Summary

Visual Inventory: Customers upload photos/video of rooms. AI estimates volume, identifies special handling items, and generates quote. 85% accuracy vs. in-home estimates.

Challenge

Solution

  • Visual Inventory: Customers upload photos/video of rooms. AI estimates volume, identifies special handling items, and generates quote. 85% accuracy vs. in-home estimates.
  • Crew Scheduling: Optimization algorithm assigns crews based on move size, distance, crew experience, and equipment needs. Maximizes daily move completions.
  • Claims Prevention: Computer vision analyzes pre-move item condition photos. Creates timestamped record reducing frivolous damage claims.

Technical Stack

Key Metrics

88%
Quote accuracy improved to 88% (reduced refunds for over-estimates)
1.3
Average daily moves per crew increased from 1.3 to 1.8
79%
In-home estimate appointments reduced 79%
43%
Damage claims reduced 43% ($28k annual savings)
2
Eliminated 2 FTE estimator roles ($62k savings)

Implementation Timeline

8 weeks including mobile app development

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