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beginnerRetail2 weeks

AI-Powered Inventory Forecasting for Boutique Store

1-10 employees

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The Problem

A fashion boutique was constantly overstocking slow-moving items while running out of popular sizes. This led to $25,000 in dead inventory and lost sales from stockouts.

The Solution

Deployed a lightweight AI inventory forecasting tool that analyzes historical sales data, seasonal trends, and local events to predict demand. The system provides weekly restocking recommendations.

Implementation Guide
Step-by-step process and timeline

Connected the AI tool to their Square POS system via API. Uploaded 18 months of historical sales data. The AI learned seasonal patterns and size preferences. Weekly reports sent via email with recommended order quantities.

Results & ROI
Quantified business impact
roi
410% in 6 months
inventory Reduction
35% reduction in excess inventory
stockout Decrease
62% fewer stockouts
profit Increase
$31,000 in 6 months
Lessons Learned
Key insights from the implementation

The AI needed at least 12 months of data to make accurate predictions. Manual adjustments were still needed for unexpected events like local festivals. The system paid for itself in the first month by preventing a $3,000 overstock order.

Pitfalls Avoided
Common mistakes and how to prevent them

Don't blindly trust AI recommendations initially. We cross-checked predictions against our intuition for the first 2 months and found the AI was 85% accurate, which built our confidence.

Cost Breakdown
setup$600 one-time
monthly$89 subscription
training$200
total$800 initial + $89/month
Tools & Technologies
  • Inventory Planner AI
  • Square POS
  • Google Sheets
Quick Stats
Industry
Retail
Company Size
1-10 employees
Timeline
2 weeks
Difficulty
beginner

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