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As modern economies become predominantly service-based, companies increasingly derive revenue from the creation and sustenance of long-term relationships with their customers. In such an environment, marketing serves the purpose of maximizing customer lifetime value (CLV) and customer equity, which is the sum of the life-time values of the company's customers. This article reviews a number of implementable CLV models that are useful for market segmentation and the allocation of marketing resources for acquisition, retention, and cross-selling. The authors review several empirical insights that were obtained from these models and conclude with an agenda of areas that are in need of further research.
Keywords: customer lifetime value; customer equity; customer retention; probability models; persistence models
Customer lifetime value (CLV) is gaining increasing importance as a marketing metric in both academia and practice. Companies such as Harrah's, IBM, Capital One, LL Bean, ING, and others are routinely using CLV as a tool to manage and measure the success of their business. Academics have written scores of articles and dozens of books on this topic in the past decade. There are several factors that account for the growing interest in this concept.
First, there is an increasing pressure in companies to make marketing accountable. Traditional marketing metrics such as brand awareness, attitudes, or even sales and share are not enough to show a return on marketing investment. In fact, marketing actions that improve sales or share may actually harm the long-run profitability of a brand. This is precisely what Yoo and Hanssens (2005) found when they examined the luxury automobile market.
Second, financial metrics such as stock price and aggregate profit of the firm or a business unit do not solve the problem either. Although these measures are useful, they have limited diagnostic capability. Recent studies have found that not all customers are equally profitable. Therefore, it may be desirable to "fire" some customers or allocate different resources to different group of customers (Blattberg, Getz, and Thomas 2001; Gupta and Lehmann 2005; Rust, Lemon, and Zeithaml 2004). Such diagnostics are not possible from aggregate financial measures. In contrast, CLV is a disaggregate metric that can be used to identify profitable customers and allocate resources accordingly (Kumar and Reinartz 2006). At the same time, CLV of current...