Maple AI Consultants

AI consulting case studies by Joel & Nanz Inc.

Beverage Distribution • 850 Restaurant Accounts

Case Study 40: Wine Distributor

Marketing-optimized case study for Canadian SMBs.

$147,000
Annual Savings
395%
ROI
3.5 months
Payback
Beverage Distribution • 850 Restaurant Accounts
Industry Focus

Executive Summary

Recommendation Engine: AI suggests wines to restaurant buyers based on menu type, price point, current list, and seasonal trends. Learns from order history.

Challenge

Solution

  • Recommendation Engine: AI suggests wines to restaurant buyers based on menu type, price point, current list, and seasonal trends. Learns from order history.
  • Order Automation: ML predicts reorder timing for each account based on historical patterns. Automated order suggestions via email with one-click approval.
  • Inventory Optimization: Demand forecasting by SKU considering seasonality, ratings, and distributor pricing. Reduces slow-moving inventory.

Technical Stack

Key Metrics

23%
Sales per account increased 23%
31%
Order frequency improved 31%
$280
Slow-moving inventory reduced from $280k to $94k
42%
Sales rep productivity increased 42%
3
Eliminated 3 FTE inside sales roles ($108k savings)

Implementation Timeline

11 weeks including historical data analysis

Ready to map your SMB workflow?

We can estimate ROI and scope the right MapleWorkSuite configuration for your team.

Start a Custom Case Study