Statistical Methods in Customer Relationship Management

1.4 Analytical Methods

Data, technology, and performance metrics combine to provide interesting insights into both the brand and the customer. However, in order to maximize the performance metrics, one has to understand the drivers/levers affecting them. For example, if a firm wants to maximize CLV, one proven strategy is to optimally allocate the marketing resources to each customer. However, this would not be possible if there were no statistical model created to link marketing activities to CLV. Thus, statistical models provide the necessary function of creating the linkage between performance metrics and the possible drivers/levers. In this book, we create many linkages through statistical models to help acquire, retain, and win back profitable customers as well as identifying customer propensity to churn. With the advent of higher computing power, the use of statistical tools is becoming a common phenomenon in all organizations.