D2C Brand Reduces Inventory Costs by 40% with AI-Powered Forecasting
The Challenge
A direct-to-consumer product startup struggled with inventory management, frequently running out of popular items while overstocking slow movers. Manual forecasting led to lost sales and excess inventory costs.
Our Approach
We developed an AI-powered inventory management system that analyzes sales patterns, seasonal trends, and market data to predict demand. The platform automates reorder points and provides real-time inventory visibility across channels.
Analyzed historical sales data to identify patterns, trends, and seasonality
Built machine learning models that predict demand for each SKU
Developed automated reorder point calculations based on predicted demand and lead times
Created real-time inventory visibility across all sales channels
Integrated with e-commerce platforms and warehouse management systems
Designed intuitive dashboards that highlight inventory risks and opportunities
Key Features
AI-powered demand forecasting for each SKU
Automated reorder point calculations
Real-time inventory visibility across channels
Multi-channel inventory synchronization
Inventory risk alerts and recommendations
Sales and inventory analytics dashboards
Impact & Results
Reduced inventory costs by 40% through accurate demand forecasting
Eliminated stockouts for top-selling products, increasing revenue by 15%
Reduced excess inventory by 50%, freeing up working capital
Automated reorder processes, saving 20 hours per week in manual work
Improved cash flow by optimizing inventory levels across product categories
Technologies & Capabilities
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Capabilities
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