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are likely to give.

The SOW metric does reveal whether or not a customer is loyal but ifused as the sole metric for resource allocation, then SOW does not take into account thesize of the budget; the metric provides a SOW percentage but does not accompany adollar amount. Finally, the PCV metric does not look directly at profitability as avariable, and makes the assumption that past spending behavior will indicate futurebehavior (Kumar, 2008b). All of these metric-specific drawbacks, coupled with theircollective lack of predictive power, can lead a firm to misallocate precious resourcesand to privileging the wrong customer or customer segment.Because of the shortcomings of the strategic customer-based value metrics, there isneed for a metric that solves the issues that are inherent within them; a metric that canaccurately predict the future profitability of a customer and strengthen resourceallocation budgets.

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The CLV metric does just that (Kumar and Reinartz, 2006; Kumarand Rajan, 2012). CLV is a forward-looking metric that does not prioritize loyaltyover profitability, meaning CLV makes certain that valuable (and not merely loyal)customers are profitable (Kumar, 2008b). Unlike the previous three categories of popularmarketing metrics, the measurement of CLV includes the likelihood of a customer beingactive in the future and the marketing dollars that need to be spent to retain the customerand achieve a positive return on investment (ROI) (Kumar, 2008a). CLV also letsmanagers “know when a customer buys, how much a customer buys and how much itcosts to make the sale (Kumar, 2008b)”.

The above-mentioned aspects of CLV make it anencompassing, revolutionary, and unique forward looking metric. Summing the CLV ofall customers leads to customer equity that forms the foundation for valuing firms(Rust et al., 2004; Schulze et al., 2012).

Additionally, competitive effects can be includedas the elements of customer equity to consider customers brand switching behavior(Rust et al., 2004). Leading indicators of behavior such as what customers think aboutthe relationship with the firm and fit between customer needs and provided services canalso be used as sources of customer equity (Zeithaml et al.

, 2006). However, customerequity and CLV do not provide every possible piece of information, and can only be usedto understand the profitability of the firm’s customers. Therefore, this paper argues forthe use of complementarity metrics. While customer equity is the most useful metric inunderstanding the value of the customer base, it should be combined with other metricssuch as the expected churn rate, expected SOW, expected failure and service recoveryrates, human resource (HR) metrics, as well as operational metrics.

Each of these metricscan provide different pieces of valuable information that can inform managers aboutthe direction their business is going into. For instance:(1) Customer engagement value (Kumar et al., 2010a, b) – this measure provides asnapshot of customer health that encompasses CLV, customer referral value,customer influencer value, and customer knowledge value.(2) Customer engagement behaviors (Van Doorn et al., 2010) – beyond atransactional basis; it is defined as a behavioral manifestation that are focusedaround a firm or a brand which is a result of motivational drivers.

(3) Expected churn rate – necessary to understand:. The degree to which retention is actually an issue..

The potential financial losses associated with customer churn.(4) Expected SOW – for firms in polygamous (simultaneous multi-brandusers) industries, it can be calculated using the wallet allocation rule

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