Profitable Customer Management: Measuring and Maximizing Customer Lifetime Value
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Loyal customers cost less to serve, pay more than other customers, and attract more customers through word of mouth. If you agree with these three claims, it is time to revisit them and find out why they may not be true. Our research has shown that loyal customers know their value to the company and demand premium service, believe they deserve lower prices, and spread positive word of mouth only if they feel and act loyal. Then why do companies pursue the claims listed above, and what is their logic in doing so? The answer lies in the premise that loyalty equals profitability. With this premise as the base, companies maximize backwardlooking metrics such as RFM (Recency of purchases, Frequency of purchases, and Monetary value of purchases), PCV (Past Customer Value), and SOW (Share of Wallet). Managing customers for loyalty, however, does not amount to managing them for profitability. On the contrary, the loyalty-profitability link must be managed simultaneously. How is this achieved? We propose that measuring and maximizing Customer Lifetime Value (CLV) will help companies address this issue. When using the CLV paradigm, companies can make consistent decisions over time about which customers and prospects to acquire and retain, as well as those not to acquire and retain, and also determine the level of resources to be spent on the various micro-segments. Further, we have found that selecting and nurturing customers based on the CLV approach increases future profitability of the customers. CUSTOMER LIFETIME VALUE: A FORWARD-LOOKING METRIC What is CLV, and how can we measure it? CLV can be defined as: "The sum of cumulated cash flows--discounted using the weighted average cost of capital (WACC)--of a customer over his or her entire lifetime with the company." Although a true CLV measure implies measuring the customer's value over his or her lifetime, for most applications it is three years. This time period is due to three reasons--product life cycle, customer life cycle, and an 80% of profit that can be accounted for in three years. Figure 1 explains the approach to measuring CLV. The CLV framework can be modeled using three main components: contribution margin, marketing cost, and probability of purchase in a given time period. Each of these models has a set of drivers and predictors, and the models are estimated simultaneously. By applying this modeling approach, managers can estimate the CLV for each customer of the firm. The calculation of CLV for all customers helps the firm rank customers on the basis of their contribution to profits. This would help firms in developing and implementing customer-specific strategies that can maximize customer lifetime profits and lifetime duration. In other words, CLV helps the firm treat each customer differently, based on his or her contribution, rather than treating all customers the same. [FIGURE 1 OMITTED] To test if CLV is really better than the backwardlooking metrics, we rank-ordered customers of a large high-tech services company from best to worst according to each metric (RFM, PCV, and CLV) using the first 48 months of data from one of our studies. We compared the total revenue, costs, and profits from the top 15% of the customers. For the next 24 months, the net value generated by the customers who were selected based on CLV score was about 45% greater than that generated by customers selected based on the traditional metrics. This shows that using CLV to select customers is far more effective than using the traditional metrics. Having identified CLV as the best metric to manage customers profitably, let us try to answer the three important questions virtually all firms in every industry typically face: 1. How do we determine which types of customers and future prospects to retain, grow, acquire, or win back? 2. How do we determine which types of customers and future prospects not to retain, grow, acquire, or win back? …