Case Study: Stylus achieves up to 98% forecasting accuracy with Promodo analytics

Stylus achieves up to 98% forecasting accuracy with Promodo

Stylus, a major electronics retailer in Ukraine, faced the challenge of accurately forecasting daily transactions and call center volume to optimize logistics, staffing, and marketing budgets. They partnered with analytics vendor Promodo to develop a solution for this critical business planning.

Promodo implemented a solution using machine learning and dedicated Python scripts, testing several forecasting models including Additive Regression and ARIMA on two years of historical data. They accounted for holidays and demand periods to refine the models, then visualized the forecasts in Power BI. This approach allowed Stylus to achieve up to 98% accuracy in its forecasting models, with a short-term error rate of only ~5%, enabling highly competent resource allocation and logistics planning.

Stylus