Rajkumar Venkatesan

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Customers can interact with and create value for firms in a variety of ways. This article proposes that assessing the value of customers based solely upon their transactions with a firm may not be sufficient, and valuing this engagement correctly is crucial in avoiding undervaluation and overvaluation of customers. We propose four components of a customer’s(More)
The authors thank the editors, guest editor, and the reviewers for their suggestions on an earlier version of the manuscript. We also thank a high technology firm for providing the data used in this study. Special thanks are owed to J. Andrew Petersen, Girish Ramani, and Srini Srinivasan for their valuable insights. We extend thanks to Renu for copyediting(More)
The authors use panel data constructed from the responses of repeatedly surveyed top managers at 261 companies regarding their firm’s market orientation, along with objective performance measures, to investigate the influence of market orientation on performance for a nine-year period from 1997 to 2005. The authors measure market orientation in 1997, 2001,(More)
Vol. XLIV (November 2007), 579–594 579 © 2007, American Marketing Association ISSN: 0022-2437 (print), 1547-7193 (electronic) *Rajkumar Venkatesan is Associate Professor of Business Administration, Darden Graduate School of Business, University of Virginia, Charlottesville (e-mail: Venkatesanr@darden.virginia.edu). V. Kumar (VK) is ING Chair Professor in(More)
C management activities at firms involve making consistent decisions over time, about: (a) which customers to select for targeting, (b) determining the level of resources to be allocated to the selected customers, and (c) selecting customers to be nurtured to increase future profitability. Measurement of customer profitability and a deep understanding of(More)
Online retailers are increasingly using information technologies to provide value added services to customers. Prominent examples of these services are online recommender systems and consumer feedback mechanisms that serve to reduce consumer search costs and uncertainty associated with the purchase of unfamiliar products. The central question we address is(More)
Despite an abundance of data, most companies do a poor job of predicting the behavior of their customers. In fact, the authors' research suggests that even companies that take the greatest trouble over their predictions about whether a particular customer will buy a particular product are correct only around 55% of the time--a result that hardly justifies(More)
Many retailers have collected large amounts of customer data using, for example, loyalty programs. We provide an overview of the extant literature on customer relationship management (CRM), with a specific focus on retailing. We discuss how retailers can gather customer data and how they can analyze these data to gain useful customer insights. We provide an(More)