Case Study: a leading US home décor brand achieves 94% product demand forecasting accuracy with Cybage's ML-based forecasting solutions

Leading US Home Décor Brand attains 94% demand forecasting accuracy with Cybage

Cybage worked with a leading US home décor brand that faced significant challenges in demand forecasting and inventory management. The client, a global retailer with a vast number of SKUs, needed to improve forecast accuracy, reduce stock-outs, and leverage data-driven insights for better decision-making.

Cybage implemented a machine learning-based forecasting solution that involved organizing raw data, performing exploratory analysis, and building a fine-tuned ML model. This solution achieved 94% accuracy in product forecasting over a 12-week period, forecasted approximately 2,600 SKUs, and identified a majority of products with negative GMROI. For the client, Cybage's work minimized stock-outs, optimized inventory levels, and enhanced overall operational efficiency.