Handbook of Research on Customer Equity in Marketing
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Handbook of Research on Customer Equity in Marketing

Edited by V. Kumar and Denish Shah

Customer equity has emerged as the most important metric to manage firm performance. This Handbook covers a broad range of strategic and tactical issues related to defining, measuring, managing, and implementing the customer equity metric for maximizing firm performance. Drawing upon the wisdom of a global pool of leading scholars, the book serves as a comprehensive and authoritative guide on customer lifetime value and customer equity for marketing researchers, practitioners, and students worldwide.
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Chapter 3: Simple probability models for computing CLV and CE

Peter S. Fader and Bruce G.S. Hardie


The past two decades have seen an evolution from transaction-oriented to customer-centric marketing strategies (Fader, 2012). As part of this shift, it is now common to think of a firm’s customers as assets that generate cash flow, not just this period but in future periods as well. This is formalized in the notion of customer lifetime value (CLV), which Pfeifer, Haskins, and Conroy (2005) define as ‘the present value of the future cash flows attributed to the customer relationship’ (p. 17). Using the term ‘customer equity’ (CE) to denote the sum of the lifetime values of a firm’s customers, Blattberg and Deighton (1996) suggested that a central goal for the marketing executive (and for the firm as a whole) should be to maximize CE. At the heart of any attempt to measure CE is the calculation of CLV, which requires us to answer two questions: (1) How long will the customer remain ‘alive’? and (2) What is the net cash flow per period while ‘alive’? This requires the analyst to make multi-period forecasts of key behaviors (i.e., for each period, is the customer still ‘alive’ and, if so, how much do they spend?). In other words, this is a time-series modeling problem.

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