Stochastic Dynamic Multi-product Pricing Under Competition

Abstract

Many firms are selling different types of products. Typically sales applications are characterized by competitive settings, limited demand information, and substitution effects. The demand probabilities of a firm’s products are affected by its own product prices as well as competitors’ product prices. Due to the complexity of such markets, effective pricing strategies are hard to derive. In this paper, we analyze stochastic dynamic multi-product pricing models under competition for the sale of durable goods. In a first step, a data-driven approach is used to quantify substitution effects and to estimate sales probabilities in competitive markets. In a second step, we use a dynamic model to compute effective heuristic feedback pricing strategies, which are even applicable if the number of competitors’ offers is large and their pricing strategies are unknown.