How to project customer retention

✍ Scribed by Peter S. Fader; Bruce G.S. Hardie

• Publisher: John Wiley and Sons
• Year: 2007
• Tongue: English
• Weight: 772 KB
• Volume: 21
• Category: Article
• ISSN: 1094-9968
• DOI: 10.1002/dir.20074

✦ Synopsis

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. We provide a detailed appendix covering the implementation details and offer additional pointers to other related models.