E-Commerce
Demand-Supply Gap
The business problem and approach
Developed a machine learning solution to identify demand-supply gaps at the zip code level for an eCommerce client, enabling optimized inventory allocation and improved market penetration. Implemented alerting and visualization tools to provide actionable insights for stakeholders to address imbalances proactively.
Implementation highlights
Predicted demand patterns using historical sales and demographic data, Built alert system to notify supply-demand imbalances in real time, Created Tableau dashboards to visualize geolocation-based gaps
Delivery and outcomes
20% improvement in market penetration, 25% reduction in lost sales due to supply shortages, 30% faster stakeholder response to supply-demand alerts
Technologies used
- Python
- Machine Learning
- SQL
- Tableau
- Azure
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