Dynamic customer management and the value of one-to-one marketing

The concept of one-to-one marketing is intuitively appealing, but there is little research that investigates the value of individual-level marketing relative to segment-level or mass marketing. In this paper, we investigate the financial benefits of and computational challenges involved in one-to-one marketing. The analysis uses data from an online grocery and drug retailer. Like many retailers, this firm uses multiple promotional instruments including discount coupons, free shipping offers, and a loyalty program. We investigate the impact of customizing these promotions on the two most important consumer decisions: the decision to buy from the store and expenditure. Our modeling approach accounts for two sources of heterogeneity in consumers' responsiveness to various marketing mix elements: cross-sectional differences across consumers and temporal differences within consumers based on the purchase cycle. The model parameter estimates are fed into a dynamic programming model that determines the optimal number, sequence, and timing of promotions to maximize retailer profits.