Forecasting and the Role of Churn in Software-as-a-Service Business Models


This article demonstrates a revenue forecasting model for Software-as-a-Service (SaaS) business models. Due to the highly predictable nature of subscriptions, a SaaS business can often project future revenue on the basis of a few key metrics. However, understanding and predicting the churn rate of the subscription base is critical to successful projections. The authors explain SaaS churn and demonstrate the use of critical variables in a predictive SaaS revenue model. The model allows a business to project future revenues based on historical and expected customer subscription behavior. The methodology combines research with the experience of a senior executive in a SaaS-driven business to build the predictive platform.

Share and Cite:

A. Sukow and R. Grant, "Forecasting and the Role of Churn in Software-as-a-Service Business Models," iBusiness, Vol. 5 No. 1A, 2013, pp. 49-57. doi: 10.4236/ib.2013.51A006.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] D. Durkee, “Why Cloud Computing Will Never Be Free,” Communications of the ACM, Vol. 3, No. 5, 2010, pp. 62-69. doi:10.1145/1735223.1735242
[2] Gartner Research, “Gartner Says Worldwide Cloud Services Market to Surpass $10.9 Billion in 2012,” 2012.
[3] Gartner Research, “Gartner Says Worldwide Softwareas-a-Service Revenue to Reach $14.5 Billion in 2012,” 2012.
[4] R. S. Randhawa and S. Kumar, “Usage Restriction and Subscription Services: Operational Benefits of Rational Users,” Manufacturing & Service Operations Management, Vol. 10, No. 3, 2008, pp. 429-447. doi:10.1287/msom.1070.0180
[5] J. Fitzgerald and J. Hynes, “Salesforce.Com Announces Third Quarter Fiscal Year 2005 Results,” 2012.
[6] D. Havlek, “Salesforce,” 2012.
[7] A. Benlian and T. Hess, “Opportunities and Risks of Software-as-a-Service: Findings from a Survey,” Decision Support Systems, Vol. 52, No. 1, 2011, pp. 232-246. doi:10.1016/j.dss.2011.07.007
[8] Bessemer Venture Partners, “Bessemer’s Top 10 Laws of Cloud Computing and SaaS,” 2010.
[9] S. Noble, “Defining Churn Rate,” 2011.
[10] T. Tzuo, “The Only Three SaaS Metrics That Matter,” 2012.
[11] R. Doctors, R. Katz, J. Berstein and B. Schefers, “Is the Price Right? Strategies for New Introductions,” Journal of Business Strategy, Vol. 31, No. 3, 2010, pp. 29-37. doi:10.1108/02756661011036682
[12] J. Espadas, A. Molina, G. Jimenez, M. Molina, P. Ramirez and D. Concha, “A Tenant-Based Resource Allocation Model for Scaling Software-as-a-Service Applications over Cloud Computing Infrastructures,” Future Generation Computer Systems, Vol. 29, No. 1, 2012, pp. 273-286. doi:10.1016/j.future.2011.10.013
[13] K. Popp, “Software Industry Business Models,” IEEE Software, Vol. 28, No. 4, 2011, pp. 26-30. doi:10.1109/MS.2011.52
[14] J. Qi, L. Zhang, Y. Liu, L. Li, Y. Zhou, Y. Shen, L. Liang and H. Li, “ADTreesLogit Model for Customer Churn Prediction,” Annals of Operations Research, Vol. 168, No. 1, 2009, pp. 247-265. doi:10.1007/s10479-008-0400-8
[15] G. Nie, W. Rowe, L. Zhang, Y. Tian and Y. Shi, “Credit Card Churn Forecasting by Logistic Regression and Decision Trees,” Expert Systems with Applications, Vol. 38, No. 12, 2011, pp. 15273-15285. doi:10.1016/j.eswa.2011.06.028
[16] H. Lee, Y. Lee, H. Cho, K. Im and Y. S. Kim, “Mining Churning Behaviors and Developing Retention Strategies Based on a Partial Least Square (PLS) Model,” Decision Support Systems, Vol. 52, No. 1, 2011, pp. 207-216. doi:10.1016/j.dss.2011.07.005
[17] K. Coussement and D. Van den Poel, “Churn Prediction in Subscription Services: An Application,” Expert Systems with Applications, Vol. 34, No. 1, 2008, pp. 313-327. doi:10.1016/j.eswa.2006.09.038
[18] J. Ahna, S.-P. Han and Y.-S. Lee, “Customer Churn Analysis: Churn Determinants and Mediation,” Telecommunications Policy, Vol. 30, No. 10-11, 2006, pp. 552-568.
[19] G. Madden, S. Savage and G. Coble-Neal, “Subscriber Churn in the Australian ISP Market,” Information Economics and Policy, Vol. 11, No. 2, 1999, pp. 195-207. doi:10.1016/S0167-6245(99)00015-3
[20] J. York, “SaaS Metrics Guide to SaaS Financial Performance,” 2010.

Copyright © 2021 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.