In the modern marketplace, the consumer holds the power. That’s especially true in the SaaS or recurring revenue realm: buyers have access to a virtually infinite array of software solutions, and saying sayonara to any one of them is as easy as clicking “cancel service.” So, how do you stop your customers from getting to that point and walking out the metaphorical door? Well, as the old saying goes, you can’t manage what you don’t measure, and in this day and age, the business metrics that provide the most actionable data are those that measure performance at the customer level. These are the data points that will tell you whether your business can sustain its current performance in the long term. And the big kahuna of customer-level metrics is—you guessed it—churn rate.
(Number of Customers Lost) ÷ (Original Number of Customers)For example, if a business started the month with 20 customers and, over the course of that month, lost one customer, then it would have a monthly churn rate of 5%. (Keep in mind that you wouldn’t include any new sales as part of this data; those customers would be part of the calculations for the next time period.) Simple enough, right? Well, sort of. Things get a bit complicated when you bring revenue into the picture. You see, there are different ways to quantify churn. And because businesses often are most interested in seeing customer retention's impact on company revenue, it can be helpful to calculate retention in terms of revenue. That’s where the customer retention formula gets more complex. To figure out your revenue churn, you’ll need to know your monthly recurring revenue (MRR)—that is, “income that a company can reliably anticipate every 30 days,” explains TechTarget. Then, divide that figure by the amount of MRR you lost over the course of a particular month. Important note: when calculating these figures, you must subtract any new revenue you generated from existing customers (i.e., from upselling and cross-selling). Including new revenue as part of the equation would skew your picture of how much revenue you actually lost, and in this case, that is the data point you’re truly after. For the purposes of this explanation, let’s assume you’re calculating everything in monthly terms. While you can calculate revenue churn for any time period, you would need to use the recurring revenue figure that correlated with the time period you chose. For example, if you were determining your quarterly revenue churn, you’d need to use your quarterly recurring revenue in place of MRR. One quick note on time period selection: if you choose to calculate customer retention for a longer time period (e.g., quarterly), then, as this evergage article explains, you’ll need to consider the fact that “some new sales from the first month in the quarter…could leave in the second or third month of the quarter. If those departures are accidentally included in the calculation, then we’ll overstate customer retention.” Here, in the interest of simplicity, we’ll look at revenue retention from a monthly perspective. Let’s take a look at an example adapted from the above-cited article. Say your MRR at the beginning of the month is $100,000. At the end of the month, it’s $80,000. During that time period, you also add $10,00 in upgrades from existing customers. So, your revenue churn rate would be:
(($100,000 – $80,000) – $10,000) ÷ $100,000 = ($20,000 – $10,000) ÷ $100,000 = ($10,000) ÷ $100,000 = 0.1 = 10%
(500 + 100) ÷ (15,000) = (600) ÷ (15,000) = .04 = 4%
To calculate your revenue churn rate, add in the associated dollar amounts: ((500 X $200) + (100 X $500)) ÷ ($4,500,000) = ($100,000 + $50,000) ÷ ($4,500,000) = ($150,000) ÷ ($4,500,000) = 0.033 = 3.3%As you can see, your customer attrition rate (4%) is slightly higher than your revenue attrition rate (3.3%). It’s important to distinguish between these two metrics because each figure provides different information about your business. Furthermore, separating out the product lines can help you see where your business is strongest in terms of customer retention and revenue generation. For example, even if you lose a relatively high number of basic service customers—thus producing a relatively high customer attrition rate—your revenue attrition rate might not look as bad, comparatively speaking. Why? Because if you are focused on retaining your premium customers (i.e., the customers with the highest monetary value), then losing some of your basic customers might not have a huge financial impact.