Leading regional airline improves demand forecasting capabilities, reduces costs, and boosts revenue with ML-powered cargo and route optimization strategies.
A leading global sports apparel brand was faced with inventory gaps, resulting in inventory carrying costs, poor customer experience, and cash flow. The company struggled to predict ever-evolving market trends in the dynamic fashion industry, and thereby impacting millions of products across several categories.
ElectrifAi helped the client look up data from multiple sources to better track product type and inventory. We helped them replace the existing approach of predicting interest in products with an attributes-based forecasting method by predicting interest in a mix of attributes. Our solution allowed the client to project future demand for all products–new or variations to existing product. The solution also allowed to generate store replenishment and store transfer recommendation at store-level based on local customer demographics.