The client is a leading brand in the home décor and organization industry, offering stylish and affordable products. With a global presence and a strong foothold in major e-commerce platforms, the company introduces hundreds of new designs monthly, serving a diverse customer base worldwide.
The client faced challenges in accurately forecasting demand and maintaining optimal inventory levels. With fluctuating customer preferences and seasonal demand, they needed a solution to:
- Improve demand forecasting accuracy across a wide range of SKUs.
- Reduce frequent stock-outs and enhance customer satisfaction.
- Optimize inventory levels to meet demand without overstocking.
- Leverage data-driven insights for better decision-making and campaign planning.
The solutions utilized machine learning and advanced data analytics to enhance demand forecasting and inventory management:
- We organized raw order data into daily, weekly, and monthly datasets to facilitate easier analysis.
- Our team generated insights through exploratory data analysis (EDA) to identify trends and patterns in the data.
- We normalized the data and tested for stationarity using the Dickey-Fuller Test, applying log differencing when needed.
- Our experts built and fine-tuned a machine learning model to provide accurate demand forecasting.
- We collected intelligent inputs from the model that helped in campaign planning and real-time decision-making, minimizing stock-outs and optimizing inventory.
