The Role of Attitudinal Information in CLV-based Customer Management
Rajkumar Venkatesan, Werner Reinartz, and Nalini Ravishanker, 2012, 12-107
The ability to build and maintain extensive behavioral databases about customers has prompted a number of firms to de-emphasize “soft” attitudinal customer information. Proponents of behavioral data argue that customer purchase behavior encapsulates underlying attitudes, and because decision makers are mainly concerned with customer behavior, attitudes do not deserve much attention.
This study questions this conventional wisdom. Rajkumar Venkatesan, Werner Reinartz, and Nalini Ravishanker determine how the inclusion of customers’ attitudes affects predictions of customer lifetime value and thus a firm’s customer management strategy. They evaluate which aspects of customer behavior – retention or sales – depend more on customer attitudes, and whether knowledge of customer attitudes is more important for managing certain customers.
On the basis of monthly sales calls, sales, and survey-based attitude information collected from customers of a multinational pharmaceutical firm over three years, the authors develop a zero-inflated Poisson model framework to model both retention and sales simultaneously. The hierarchical structure of the model allows for the influence of attitudes on retention and sales.
The results show that information on customer attitudes can help companies both explain and predict customer responses better (sales and retention). The positive effect of better attitudes on lifetime value works predominantly through the retention aspect. This implies that firms should consider customer retention rates rather than sales for any campaign focused on improving the customer’s emotional attachment.
Furthermore, the study suggests that the incremental profits from including customer attitudes in lifetime value and resource allocation models are greatest for mid-tier customers. These customers’ attitudes provide a forward-looking measure that can effectively discriminate mid-tier customers with the potential to grow from those whose profitability is likely to decrease. The study therefore suggests that firms may be actually overspending on top-tier customers. When customer attitude information is available, firms can improve the ROI of their CRM campaigns by balancing resources between top- and mid-tier customers.
Overall, in this study’s context, the projected incremental profits from a customer management strategy informed by customer attitudes exceed the investment required to collect customer attitudes. The authors therefore encourage firms to explore avenues for measuring customer attitudes and including this information in their customer management strategy.
Rajkumar Venkatesan is Bank of America Research Associate Professor of Business Administration, Darden Graduate School of Business, University of Virginia. Werner Reinartz is Professor of Marketing, University of Cologne. Nalini Ravishanker is a Professor and the Undergraduate Program Director in Statistics, University of Connecticut.
The authors thank a multinational pharmaceutical firm for sharing the customer data used in this study. They also thank participants at the 2009 Joint Statistical Meeting Conference and the 2010 Marketing Science Conference; seminar participants at the University of Groningen and University of Maryland; and Sunil Gupta, Peter Verhoef, Pete Fader, Harald van Heerde, Casey Lichtendahl, V. Kumar, Giandomenico Sarolli, Partha Krishnamurthy, Ian Skurnik, Paul Farris, Ron Wilcox, and Prashant Malaviya for their comments on previous versions of this manuscript.
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