Stockpiling Points in Linear Loyalty Programs

Abstract

Customers often stockpile reward points in linear loyalty programs (i.e., programs that do not explicitly reward stockpiling) despite several economic incentives against it (e.g., the time value of money). The authors develop a mathematical model of redemption choice that unites 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. These motivations are economic (the value of forgone points), cognitive (nonmonetary transaction costs), and psychological (customers value points differently than cash). The authors capture the psychological motivation by allowing customers to book cash and point transactions in separate mental accounts. They estimate the model on data from an international retailer using Markov chain Monte Carlo methods and accurately forecast redemptions during an 11-month out-of-sample period. The results indicate substantial heterogeneity in how customers are motivated to redeem and suggest that the behavior in the data is driven mostly by cognitive and psychological incentives.

The Role of Big Data and Predictive Analytics in Retailing

“…In retailing, the ability to track new customers and to link transactions over time is key. Loyalty programs Stourm et al 2015), widespread today, are the most common way that such tracking exists; however, credit card, IP address, and registered user log-ins are also commonplace. Besides more rows, firms also have much better measures (columns) about each row which typically, in retailing, might include a link between customer transaction data from a CRM system, demographic data from credit card or loyalty card information, survey data that is linked via email address, and instore visitation information that can be tracked in a variety of ways.…”

Reward redemption effects in a loyalty program when customers choose how much and when to redeem

“…Moreover, recent psychological insights indicate that goal-pursuit may not be the only mechanism driving LP behavior (Henderson, Beck, & Palmatier, 2011;Wiebenga & Fennis, 2014). The findings of Stourm et al (2013) indicate that in the absence of firm-driven restrictions on the amount and timing of redemption, members may form latent thresholds of redemption based on their subjective perceptions of their points' value relative to cash. Therefore, the points-pressure mechanism alone may not be sufficient in explaining the impact of redemption on pre-reward purchase behavior.…”

“…In LPs with continuous and linear rewarding schemes, members obtain a certain amount of LP currency for each dollar/euro spent and choose when to redeem (redemption timing) and what to redeem (redemption amount), based on their personal reward preferences and the collected balance of points (cf. Stourm, Bradlow, & Fader, 2013). Moreover, in continuous LPs, the program itself and/or its points typically do not expire for a longer period of time (e.g., retail LPs).…”

“…Finally, redemption effects on purchase behavior may vary across LP members (Kopalle, Sun, Neslin, Sun, & Swaminathan, 2012;Stourm et al, 2013;Zhang & Breugelmans, 2012). In particular, the effects may be moderated by members' prior experience with the LP (length of LP membership) and various socio-demographic aspects (age, income, etc.…”

Can Non-Tiered Frequency Reward Programs Be Profitable?

“…Many papers consider only the behavior of consumers during a time period after the program has started (Bolton et al, 2000;Verhoef, 2003). Other papers consider only the behavior of consumers who are in the program (Hartmann and Viard, 2008;Kopalle et al, 2012;Stourm et al, 2015), or even a subset of members consisting of the most-involved members (Lewis, 2004;Liu, 2007). In general, one cannot measure the impact of a rewards program by comparing the behavior of members and non-members because the choice to join a program is likely to be correlated with the customer's expected level of engagement with the company.…”