A Relationship Account of Marketing Rewards: the Effect of Conditional Vs. Unconditional Rewards on Self-Brand Connection

In this research we explore how rewards can be used to foster brand-self connection. Data from a field study and two laboratory experiments provide systematic evidence for how conditional versus unconditional rewards affect brand-self connection, and shed light on the underlying psychological process

Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models

The authors express their gratitude to Sanyin Siang (Managing Director, Teradata Center for Customer Relationship Management at the Fuqua School of Business, Duke University); research assistants Sarwat Husain, Michael Kurima, and Emilio del Rio; and an anonymous wireless telephone carrier that provided the data for this study. The authors also thank participants in the Tuck School of Business, Dart-mouth College, Marketing Workshop, for comments and the two anony-mous JMR reviewers for their constructive suggestions. Finally, the authors express their appreciation to former editor Dick Wittink (posthumously) for his invaluable insights and guidance. This article provides a descriptive analysis of how methodological factors contribute to the accuracy of customer churn predictive models. The study is based on a tournament in which both academics and practitioners downloaded data from a publicly available Web site, estimated a model, and made predictions on two validation databases. The results suggest several important findings. First, methods do matter. The differences observed in predictive accuracy across submissions could change the profitability of a churn management campaign by hundreds of thousands of dollars. Second, models have staying power. They suffer very little decrease in performance if they are used to predict churn for a database compiled three months after the calibration data. Third, researchers use a variety of modeling "approaches," characterized by variables such as estimation technique, variable selection procedure, number of variables included, and time allocated to steps in the model-building process. The authors find important differences in performance among these approaches and discuss implications for both researchers and practitioners

Refocusing Loyalty Programs in the Era of Big Data: A Societal Lens Paradigm

Big data and technological change have enabled loyalty programs to become more prevalent and complex. How these developments influence society has been overlooked, both in academic research and in practice. We argue why this issue is important and propose a framework to refocus loyalty programs in the era of big data through a societal lens. We focus on three aspects of the societal lens-inequality, privacy, and sustainability. We discuss how loyalty programs in the big data era impact each of these societal factors, and then illustrate how, by adopting this societal lens paradigm, researchers and practitioners can generate insights and ideas that address the challenges and opportunities that arise from the interaction between loyalty programs and society. Our goal is to broaden the perspectives of researchers and managers so they can enhance loyalty programs to address evolving societal needs

Discrete and Continuous Representations of Unobserved Heterogeneity in Choice Modeling

We attempt to provide insights into how heterogeneity has been and can be addressed in choice modeling. In doing so, we deal with three topics: Models of heterogeneity, Methods of estimation and Substantive issues. In describing models we focus on discrete versus continuous representations of heterogeneity. With respect to estimation we contrast Markov Chain Monte Carlo methods and (simulated) likelihood methods. The substantive issues discussed deal with empirical tests of heterogeneity assumptions, the formation of empirical generalisations, the confounding of heterogeneity with state dependence and consideration sets, and normative segmentation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46977/1/11002_2004_Article_230988.pd

The Interrelationships Between Brand and Channel Choice

We propose a framework for the joint study of the consumer's decision of where to buy and what to buy. The framework is rooted in utility theory where the utility is for a particular channel/brand combination. The framework contains firm actions, the consumer search process, the choice process, and consumer learning. We develop research questions within each of these areas. We then discuss methodological issues pertaining to the use of experimentation and econometrics. Our framework suggests that brand and channel choices are closely intertwined, and therefore studying them jointly will reveal a deeper understanding of consumer decision making in the modern marketing environment