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

Anthony E. R. Sukow, Rebecca Grant

Advanced Ecommerce Research Systems Inc., Palo Alto, CA, USA.
Gustavson School of Business, University of Victoria, Victoria, B.C., Canada.

DOI: 10.4236/ib.2013.51A006                

Abstract

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.

Keywords

SaaS; Churn; Software; Subscription; Revenue Forecasting

Conflicts of Interest

The authors declare no conflicts of interest.

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