Too many marketing managers fail to identify their most valuable customers. They are either spending their marketing dollars on the wrong customers or in the wrong channels of communication.

Here is a framework for measuring customers' lifetime value and a road map of how a customer's lifetime value can guide marketing managers in making three key decisions: Which customers should we contact? What channel should we use to contact them? How much contact should we have with customers?

Typically, customer metrics such as Past Customer Revenue (PCR), and Past Customer Value (PCV) are used to identify profitable customers. But these metrics are backward-looking; they do not provide a future picture of customer profitability.

Instead, measures like Customer Lifetime Value (CLV) provide a forward-looking picture. But less is known about the factors that affect CLV—and about the cost of maximizing CLV.

Using rich customer transaction data from a large multinational firm, we evaluated the usefulness of CLV and now present it as a metric that marketers can use to understand customers and optimize the return on marketing investments.

Significance of the Research

This research is of great significance to the burgeoning practitioner literature on customer relationship management. Many firms tout their capabilities to offer complete "360-degree" coverage of customer behavior, but they fail to effectively utilize that customer information in designing marketing strategies.

While we focus on one of the many possible benefits that can arise from rich customer information, the same modeling approach can be applied to other related domains—such as cross-selling multiple products to a customer, managing customers across channels and acquiring prospects.

Often, marketing managers are faced with this situation: The available marketing budget prohibits them from contacting all their current customers and potential prospects. This has led them to use several heuristics to select the customer to be contacted.

For example, some firms rank-order customers based on their past revenue and select only the top 20% of the customers from this rank-ordered list. This process is termed as customer selection. But there is no clear guidance in the marketing literature on which metric identifies the future stars among customers.

Marketing managers are also faced with resource limitations in contacting their customers through all the available channels. Managers have a need for appropriate resource allocation strategies. The marketing literature provides very little insight into decisions about how to manage individual customers in a way that accounts for dynamic updating of profitability assessment.

We looked at the above challenges faced by marketing managers and compared the capability of the customer metrics in identifying customers who would become future stars. We provide a framework for determining the optimal level of marketing resources for each individual customer that would maximize the overall profits obtained from a firm's customers.

Implications of the Research for Marketing Practice

We made recommendations on three aspects: first, on the superior selection of profitable customers; second, on discovering customer contact preferences; and third, on the superior design of the marketing campaign to reach those profitable customers.

Aspect 1: Superior selection of profitable customer

For the first aspect, we offer a model to estimate the lifetime value of each customer based on factors like cash flows, inter-purchase times, and variable marketing costs. We then compare the performance of the CLV metric with the performance of PCR, PCV and Customer Lifetime Duration (CLD) by ranking customers from best to worst according to each measure, and then comparing the future sales, costs and profits of the top 5%, 10% and 15% of customers.

The study concludes that CLV is better at identifying profitable customers than either of the other metrics.

Net profits obtained from the top 5% of the customers selected based on lifetime value was about two times the net profits obtained from those selected based on PCR; 1.3 times the net profits obtained from customers selected based on CLD; and 1.1 times the net profits obtained from those selected based on PCV. The difference in profits resulting from the use of PCV, PCR, and CLD on the one hand, and CLV on the other, averages $40,000 for a customer in the top 5%.

Aspect 2: Discovering customer contact preferences

Customers have different preferences for how they wish to be contacted. Some prefer being contacted by salespeople, because the interaction is very rich and the salesperson can answer any queries that they have. But other customers prefer obtaining product information through a brochure or email. Recognizing customer contact preferences goes a long way toward earning a customer's trust and ensuring future business.

We also found that that there is an optimal level of marketing communication for each customer. A firm's increasing communication beyond a certain threshold may result in customers' decreasing their customer purchase frequency. The research also finds that, in general, customers react more negatively when over-contacted by a salesperson rather than by direct mail. Therefore, although contact through sales personnel is interactive and effective, firms should use it with great caution.

Aspect 3: Superior design of the marketing campaign

Having selected their most promising customers, managers must allocate resources in a way that maximizes their profitability. Thus, the third aspect of the study identifies the superior design of marketing communication for individual customers based on their CLV.

Using CLV to target customers for cost cutting and resource allocation offers substantial improvement over current resource allocation rules. In the study, superior design increased profits 67% (from $28 million to $47 million) while increasing the cost of serving customers only 34% (from $233,000 to $314,000). The study enables managers to design a communication strategy that best suits a customer's preferences and at the same time does not exceed the customer's expected value potential.

Overall, we found that by targeting the right customers with an optimal marketing communication strategy, managers can realize substantial increases in profits without any major increases or decreases in marketing investments.

Note: This article is excerpted from the original, "A Customer Lifetime Value Framework for Customer Selection and Resource Allocation Strategy," which appeared in the Journal of Marketing, 68 (October), 106-25. It is reprinted with permission from the Association for Consumer Research.

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Rajkumar Venkatesan and V. Kumar are with the University of Connecticut.