Motivated by the empirical evidence observed from the real-world dataset, this paper studies context-based dynamic pricing with separable demand models. Consider a seller selling products over a finite horizon of $T$ periods and facing an unknown expected demand function that admits a separable...

We study the classic multi-period joint pricing and inventory control problem in a data-driven setting.In this problem, a retailer makes periodic decisions on the prices and inventory levels of an item that she wishes to sell. The retailer's objective is to maximize the expected profit over a...

We present our work with a global online fashion retailer, Zalando, as an example of how a global retailer can utilize massive amount of data to optimize price discount decisions over a large number of products in multiple countries on a weekly basis. Given demand forecasts under a collection of...