Dynamic pricing of omnichannel inventories

Omnichannel retail refers to a seamless integration of an e-commerce channel and a network of brick-andmortar stores. An example is cross-channel fulfillment which allows a store to fulfill online orders in any location. Another is price transparency, which allows customers to compare the online price with store prices. This paper studies a new and widespread problem due to omnichannel retail: price optimization in the presence of cross-channel interactions in demand and supply, where cross-channel fulfillment is exogenous. We model the omnichannel pricing problem as a dynamic stochastic program. We propose two pricing policies that are based on the idea of “partitions” to the store inventory that approximate how this shared resource will be utilized. These policies are practical, since they rely on solving computationally tractable mixed integer programs that can accept various business and pricing rules. Moreover, in extensive simulation experiments, they achieve a small optimality gap relative to theoretical upper bounds on the optimal expected profit. The good observed performance of our pricing policies results from managing substitutive channel demands in accordance with partitions that rebalance inventory in the network. A proprietary implementation of the analytics is commercially available as part of the IBM Commerce Markdown Price Solution. The system results in an estimated 13.7% increase in clearance period revenue based on causal model analysis of the data from a pilot implementation for clearance pricing at a large U.S. retailer.