The figure above shows the event histories of a random sample of newspaper customers. Yellow marks a period of rebate subscription, while green marks a full price subscription. Red denotes a period of no subscriptions - the customer has churned. Read more in "Analyzing Customer Lifetime Value Using Tree Ensembles" (link).
Analysis based on the customer lifetime value concept must typically account for two main aspects of customer behavior: The lifetime of a customer and the monetary value generated while active.
Given a set of customer attributes, such as demographic data and past transactions, a model of customer lifetime value can be created. The model seeks to relate customer attributes to lifetime and value.
An example of a basic quantitative approach is to model value through a linear regression model, while lifetime is estimated based on, say, an exponential distribution.
A customer lifetime value model has several exciting applications.
- Resource Prioritization. Sensible lifetime value estimates can serve as a basis for organizational resource prioritization: Customer service level design, marketing spending, sales force pay and so on.
- Novelty Detection. Detect and react to changes in the marketplace by monitoring the formation of new patterns in customer lifetime value. Are former valuable clients all of a sudden churning at higher rates? Are new groups of high value clients forming?