How to Calculate Churn Rate: A Better Formula
What is churn rate? While there is no single, industry-wide definition, any subscription business knows churn rate is a critical metric of success.
In this blog post, we’ll be discussing customer churn rate and how we calculate it at Recurly.
In the subscription industry, a general churn rate definition is the measure at which your customers stop subscribing to your service, but there are different opinions on how it is calculated. The most basic calculation of a monthly customer churn rate is the number of customers who churned in the month divided by total number of customers in the month.
Monthly Customer Churn Rate = # of Customers Who Churned in the Month / Total Number of Customers in the Month
But how do you count the total number of customers in a month? Some companies use the number of customers at the beginning of the month, while others will wait until the end of the month or take the average number of customers at the start and end of the month.
All of these definitions can lead to problems, especially for companies with lots of new customers. Let’s look at an example where the same customer behavior in two different months leads to significantly different churn rates.
The Basic Churn Rate Formula
Let’s start a fictional subscription business: Butter of the Month. Every month, we deliver a delicious, new variety of butter to our customers.
Butter of the Month starts in July with 1,000 customers. Of these original customers, 5% leave by the end of the month. We also added 500 new customers—12 of whom leave by the end of July. By the basic definition, our churn rate is 6.2%.
Now, let’s imagine we have the same customer behavior in August. We start with the 1,438 customers from the end of July (of whom 5% churn), add 500 new customers and lose 12 of them. The basic definition produces a 5.8% churn rate in August.
Hooray, our churn rate went down! August must have been a great month. But, in reality, there was no difference in customer behavior. We started August with more customers than in July, which increased the denominator.
A metric that changes based on similar inputs is unreliable, and we don’t want to make important decisions about our business based on this data.
Stephen Noble at Shopify proposes a better solution (our example is adapted from his post). Think of churn rate as a probability - how many customers churned, and how many opportunities did they have to churn?
Every day that a customer keeps her subscription is another day she doesn’t churn. If she was your customer for seven days and churned on the seventh day, she had seven opportunities to churn and exercised that option on one of the seven days. Another way to think about this is that she churned on 1/7 of the days that she could have churned.
We can aggregate that probability across all of our customers and come up with a more accurate churn rate by calculating the total number of customer days in the month.
A customer day is one day that one customer has an active subscription. In this example, we’d count the number of days in July that each customer had an active subscription, then sum that number across the entire business.
A Better Churn Rate Formula
Let’s go back to our fictional company, Butter of the Month:
A churn rate calculation starts with the number of customer churns in July—the same as before. Then, we divide by the total number of customer days in July. The result is churns per customer day.
Churns per customer day is a little difficult to unpack, so we multiply by the number of days in the month, which is 31 in this case. The result is a churn rate of 5.1%.
Where does the 0.5 in “Customer days in month” come from? For Butter of the Month, we’re assuming that the new subscriptions and churns occur at a constant rate throughout the month. In other words, the net gain of customers is linear. With that assumption (and the formula for the area of a triangle), we calculate the number of customer days:
Customer Churn Calculation
Another way to think about the 0.5 in this formula is that the new customers and the churned customers are, on average, active half the month.
Remember that this assumption is just for our fictional company. For Recurly’s dashboard, we calculate customer days by summing the actual number of subscribers that were are on each day.
So, how does this formula hold up in August?
As you can see, the churn rates for July and August are now in line. Same behavior, same result.
It’s true that this churn rate definition is more complex than the basic definition. However, we believe it forms a better basis of comparison between different time periods. And, ultimately, it gives you a better picture of your monthly subscriber churn.