Maple AI Consultants

AI consulting case studies by Joel & Nanz Inc.

Home Services • 480 Residential Accounts

Case Study 54: Pool Service Company

Marketing-optimized case study for Canadian SMBs.

$87,000
Annual Savings
510%
ROI
2.2 months
Payback
Home Services • 480 Residential Accounts
Industry Focus

Executive Summary

Water Chemistry Prediction: ML analyzes historical test data, weather patterns, and pool characteristics to predict chemical needs. Optimizes chemical inventory on service trucks.

Challenge

Solution

  • Water Chemistry Prediction: ML analyzes historical test data, weather patterns, and pool characteristics to predict chemical needs. Optimizes chemical inventory on service trucks.
  • Route Optimization: Dynamic routing considers traffic, appointment windows, and equipment needs. Automatically adjusts for cancellations and emergency calls.
  • Equipment Failure Prediction: AI analyzes service notes and equipment age to predict pump, heater, and automation failures. Proactively schedules replacements during regular service.

Technical Stack

Key Metrics

18
Service stops per technician increased from 18 to 24 daily
31%
Chemical usage optimized (waste reduced 31%)
47%
Emergency service calls reduced 47%
$142
Equipment upsell revenue increased $142k annually
28%
Fuel costs reduced 28%

Implementation Timeline

8 weeks including historical data analysis and IoT pilot

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