Back to Case Studies
Retail
Demand Forecasting for E-commerce Platform
Growing E-commerce Platform10 weeks
The Challenge
Inventory chaos affecting profitability
- Frequent stockouts on popular items losing sales
- Excess inventory tying up capital
- Seasonal patterns difficult to predict manually
- New product launches with no historical data
Our Solution
Deep learning model combining internal and external signals
- Transformer-based model processing 2 years of sales data
- External signals: weather, events, competitor pricing
- Cold-start predictions for new products using embeddings
- Daily automated retraining with drift detection
The Impact
Significant bottom-line improvement
-31%
Carrying Costs
-45%
Stockouts
89%
Forecast Accuracy
+12%
Revenue Impact
Technologies Used
PythonPyTorchApache AirflowAWS BedrockRedshift