Optimal Pricing of Seasonal Products in the Presence of Forward-Looking Consumers

We study the optimal pricing of fashion-like seasonal goods, in the presence of forwardlooking (strategic) customers, characterized by heterogeneous valuations that decline over the course of the season. We distinguish between two classes of pricing strategies: Inventorycontingent discounting strategies, and announced fixed-discount strategies. For the first class, we find a subgame-perfect Nash equilibrium for the game between the seller and the customers. For the second class, we develop an optimization problem for the seller, taking into account the consumers’ response to any feasible pre-committed price path. When inventory is limited, strategic consumers need to consider not only future prices, but the likelihood of stockouts, which depends on other customers’ behavior. Under both classes of pricing strategies, we show that it is optimal for the consumers to purchase according to individual thresholds that depend on personal base valuations and arrival times to the store. We conducted a numerical study to explore the way by which strategic consumer behavior impacts pricing policies and expected revenue performance, and to examine the way by which it interferes with the drivers of the benefits of price segmentation. We discuss the way by which equilibrium in the contingent pricing case is affected by various key factors. We also examine the performance of announced fixed-discount strategies, and argued that pre-commitment can bring an advantage to the seller, of up to 8.32% increase in expected revenues. Unlike the case of myopic customers, under strategic consumer behavior, inventory has a significant impact on the announced depth of discounts, particularly when the rate of decline in valuations is low-to-modest. Finally, we considered the case in which the seller incorrectly assumes that strategic customers are myopic in their purchasing decisions. This misperception can be quite costly, reaching a loss of 20% in expected revenues.