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How to project customer retention
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 ten...
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Published in: | Journal of interactive marketing 2007, Vol.21 (1), p.76-90 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | 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. |
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ISSN: | 1094-9968 1520-6653 |
DOI: | 10.1002/dir.20074 |