New Insights From Emerging Types of Retail Loyalty Programs

In a standard loyalty program, a single retailer offers rewards to customers who stockpile points up to a certain amount. While research on these archetypal loyalty programs is vast, there is an increasing trend for companies to adopt reward programs that do not explicitly incentivize customers to return in order to “cash-in” rewards. Two examples are linear and coalition reward programs. In a linear program, points can be redeemed at anytime for any amount. In a coalition program, points can be earned and redeemed across several partner retail stores. A chapter titled “Stockpiling Points in Linear Loyalty Programs”, uses transaction data from a linear loyalty program in Latin America to examine why customers tend to stockpile points for long periods of time, despite economic incentives against doing so (i.e., time value of money). A mathematical model of redemption choice posits three explanations for why customers seem to be motivated to stockpile on their own, even though the retailer does not reward them for doing so: economic (value of forgone points), cognitive (nonmonetary transaction costs), and psychological. The psychological motivation is captured by allowing customers to book cash and point transactions in separate mental accounts. The results indicate substantial heterogeneity in how customers are motivated to redeem and suggest that behavior in the data is driven mostly by cognitive and psychological incentives. A chapter titled “Market positioning in a coalition loyalty program: the value of a shared reward currency” uses a model of multi-store purchase incidence to infer the market positioning among popular partners of a coalition loyalty program. The model shows how the value of a rewards currency that is shared among partner stores can explain patterns in customer-level purchases across the stores, and how these reward spillovers are driven by (1) differences in reward redemption policies among the partners, (2) product category overlap between stores and (3) geographic distance between them. By leveraging a devaluation of the program's points that occurred in our observation period, we demonstrate how the value of coalition points influences the positioning of partner stores within the network.