At the heart of any contractual or subscription-oriented
business model is the notion of the retention rate. An
important managerial task is to take a series of past
retention numbers for a given group of customers and
project them into the future to make more accurate
predictions about customer tenure, lifetime value, and
so on. As an alternative to common “curve-fitting”
regression models, we develop and demonstrate a
probability model with a well-grounded “story” for the
churn process.We show that our basic model (known as a
“shifted-beta-geometric”) can be implemented in a simple
Microsoft Excel spreadsheet and provides remarkably
accurate forecasts and other useful diagnostics about
customer retention. pdf
