You know a key to running your business successfully is constantly seeking ways to improve. But how do you determine which adjustments you make result in the biggest impact? That’s where revenue retention analysis can help.

The purpose of a revenue retention analysis is to understand how groups of economic units behave and contribute revenue to a company over time. For SaaS/subscription companies that sell directly to customers, the “economic unit” is a customer, and by tracking whether groups of customers contribute more or less revenue over a specific period of time your company can identify any trends and patterns that exist.

Put to use in this way, a revenue retention analysis can be especially helpful in determining the effectiveness of any internal improvements (to your product, onboarding process, customer service, etc.) your company has attempted to implement.

The first step is to divide customers into cohorts based on their month, quarter, or year of sign-up so that you can easily compare the behavior of customers who signed up before a major initiative took place with customers who signed up afterwards.

For example, if you find that since completing a market segmentation analysis and focusing marketing/sales on that segment, the revenue retention of the most recent cohorts has dramatically improved, it may make sense to continue focusing on that market segment. It is important to remember, though, that revenue retention of any cohort is the result of many variables, many of which a company can’t control (economic conditions, competitiveness of market, etc.), so be careful about jumping to specious conclusions.

It may also be useful to take a more comprehensive approach by searching for any overperforming cohorts over a larger period of time and investigating what, if anything, the company did differently in that period (improved customer service, finding better target segments to focus on and sell to, etc.). This should help your company identify initiatives to repeat or continue. Similarly, identifying underperforming cohorts and figuring out why they are underperforming gives you the opportunity to improve the revenue retention of those cohorts and avoid any similar mistakes in the future.

A Quick Case Study

Problem:

A year ago, company X realized that a lot of its customers were churning within the first six months of sign-up and wanted to understand why. Upon conducting a market segmentation analysis, it concluded that the prospects it was targeting were too small, and from interviews, found that many were canceling their subscriptions because the benefits they received from using the product did not justify the costs. The company decided to change strategy and focus on larger prospects. Over a year later, it wanted to understand whether this shift was paying dividends and started by conducting a revenue retention analysis.

Solution:

The company undertook a revenue retention analysis in which they created two cohorts — customers acquired during the year before the strategy shift, and customers acquired in the following year. The company then compared the total revenue/billings by month, average customer bill by month, and monthly billings as a percentage of first month bill of the two cohorts.

Result:

The company found that while the number of customers it signed up in year 2 was half of year 1, the average first month customer bill was 4 times as large as the previous year, meaning that the total billings in month 1 in the year 2 cohort was twice as large as that of the year 1 cohort. Furthermore, they found that revenue retention had significantly improved from -8% per month in the first cohort to +2% per month in the second cohort (meaning that in year 2, customer upsells outweighed churn). The revenue retention analysis validated their change in strategy, and today, the company has stronger revenue growth, a more capital efficient distribution model, and has become profitable.