Revenue Retention Analysis: Why It’s Important for Your SaaS Business

May 6, 2010

Over the course of the last four years, I’ve conducted numerous revenue retention analyses for our expansion stage prospects and portfolio companies. In this series of blog posts, I will explain what the analysis shows, why this analysis is important for SaaS companies (and for most subscription-based companies), provide a step-by-step guide for conducting the analysis, and lastly, explain how to interpret the results.

The purpose of a revenue retention analysis is to better understand how groups of SaaS subscription customers (typically grouped by month, quarter, or year of sign up) behave over time. The reason we distribute customers into groups (or cohorts) based on sign-up period is so that we can easily compare, for example, the revenue retention in the first three months of the Q1 cohort to the revenue retention in the first three months of the Q2 cohort. Through the analysis, we hope to answer questions such as whether customers that signed up in Q1 2009 spend more or less over time, or some combination of the former and latter. Do a lot of customers cancel their subscription after the first month, causing a significant decrease in revenue in month 2? Do the remaining customers purchase more subscriptions/usage over time, causing steady revenue growth from that cohort after month 2? How does the behavior of Q1 customers compare to the customers who signed up in Q2, Q3, and so on?

A revenue retention analysis tells an insightful story about a subscription business and the behavior of its customers over time. It can reflect the effectiveness of a company’s efforts to improve product, increase upsells, and improve customer service. I think it is even more powerful than a customer churn analysis (which only shows attrition as a percentage of total customers), because the revenue retention analysis incorporates the effect of upsells, and weights the customers by their monthly spend (each customer’s “weight” is based on their monthly spend or revenue contribution). By contrast, a customer churn analysis treats all customers equally (regardless of monthly spend) and ignores upsells. Further, if we combine a revenue retention analysis with the sales and marketing costs needed to acquire each of the customer cohorts (for example, how much was spent in sales and marketing to acquire the Q1 customers), we also start to get a good understanding of the distribution economics of the business.

Beyond the insights you will gain, conducting the analysis will be helpful if you want to raise expansion capital. Many venture capital firms will do this analysis at some point during the due diligence process, and presenting it to them up front will save them time and likely impress them with your “metrics-driven approach” to management.

In the next few blogs, I will describe how to prepare, conduct, and interpret the results of a revenue retention analysis.

CEO

Vlad is a CEO at <a href="http://www.scan-dent.com">Scandent</a>, which develops radio frequency identification (RFID) systems that prevent theft, loss, and wandering/elopement in hospitals and nursing facilities. Previously, he was an Associate at OpenView.