Machine Learning Models to Optimize Product Distribution With the Help of Analytics
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Increase in profitability.
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Decrease in unavailable product requests across the board.
The Process
The client is a leading global retailer; the focus of the work done was for the Indian operations of the retailer. They have approximately 2,000 stores spread across the country. Different store locations have diverse customers, different weather, and varying capacity to stock and display products, which resulted in very different needs.
The initial product distribution was one size fit all for specific geographies, which resulted in under-inventory in some locations and over-inventory in others.
The Solution
Artificial Intelligence (AI) is ideal for optimizing product distribution for retailers. We created an AI model using Aiwozo for the client, which looked at a variety of factors like past sales, weather forecasts, local trends, and store display space availability.
The model optimized the product distribution by sending more inventory to stores where more products were being sold. The AI model also tracked sales in real-time and was able to predict whenever rerouting of inventory was required from one store to another.
Challenges Addressed
Key business and operational challenges that limited performance, scalability, and governance before automation was introduced.
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Out of stock issues -
Manual process -
Low customer satisfaction
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Discounts impacted profitability -
Higher retail space requirement