Data-Driven Trade Promotion Optimization for RevenueManagement in the Footwear Industry: A Case Study of Adidasand WestGear

This paper presents a comprehensive study on optimizing trade promotions in the footwear industry,focusing on the partnership between Adidas, a renowned manufacturer, and GearWest, a leadingretailer. The research explores the application of data-driven decision-making techniques, machinelearning, and revenue management to design effective trade promotions. Utilizing a dataset spanning atwo-year period and employing various ML algorithms, we predict demand and assess the performanceof different pricing strategies. The proposed model achieves a substantial increase in revenues comparedto traditional off-invoice discounts. Additionally, we discuss the implications of our findings andhighlight future research targets

کلیدواژه ها:

Trade Promotion Optimization ، Machine Learning ، Demand Forecasting ، Pricing Strategy ، Revenue Management ، Supply Chain.