The customer lifetime value, variously abbreviated as CLV or CLTV and also called lifetime customer value (LCV) as well as lifetime value (LTV), has become an important customer metric for businesses since its introduction in the late 1980s. In concept, the CLV is a predictive measure of the expected revenue or profit for a customer or group of customers over the entire lifespan of their relationship with a business.
While there is no universal methodology by which the CLV is constructed, at least there are not any approved by the Marketing Accountability Standards Board (MASB), this has not stopped the CLV from becoming widely adopted by Fortune 500 firms and other businesses. The reason for this is that the CLV confers a number of benefits including the ability to estimate, analyze, and/or justify customer acquisition/marketing strategies and costs, as well as the ability to segment customers into groups based upon their value to the business.
This recipe provides one methodology for calculating a predictive value for the CLV and demonstrates how this can be used to identify the most valuable customers to a business. Our goal is to create a measure that provides a measure of the CLV for individual customers as well as one that works in the aggregate to provide the average CLV for groups of customers. In addition, we want our CLV measure to work for different time periods of source data. In other words, our measure should be able to handle source data for customer sales over a single year or multiple years and still provide the correct calculation.