You can use a number of common methods to calculate churn rate. These range from the simple to the complex.
The simplest way to calculate churn rate is to divide the number of customers who churn over a given period by the number of customers you had at the beginning of the time frame:
Churn rate = Churned customers / Total initial customers
The result is multiplied by 100 to convert it to a percentage.
To illustrate how this formula is applied, let’s say you started the month with 200 customers. Over the course of the month, you lost 20 customers while gaining 10. Your churn rate would be 20/200, equivalent to 10%.
The above method gives you a simple way to calculate churn. It works in simple situations, but it proves less useful if your number of customers is changing quickly because of rapid growth. For example, if your customer base suddenly went from 100 to 1,000 customers over the course of the month, a 2% churn rate would have a significantly different impact on your revenue at the end of the month than at the beginning.
To address this, you can use an alternate version of the formula which uses your average number of customers over a given time frame instead of your initial number of customers. You can find your average number of customers by taking your initial and final number of customers and dividing by 2:
Churn rate = Churned customers / [(Total initial customers + Total final customers) / 2 ]
To illustrate this formula, let's say you started the month with 300 customers and ended with 200. Your churn rate would be 100 / [(300 + 200) / 2] = 100/250 = 0.4, or 40%. In contrast, if you were using the basic churn formula for this scenario, your churn rate would be 100/300, or about 67%, painting a significantly different picture.
This alternate version of the churn rate formula is often used to average churn over the course of a month. This can give a more accurate picture of churn than only going by the beginning of the month.
Just as churn calculations can be averaged over the course of a month for greater accuracy, they can be averaged over even smaller intervals for still finer approximations.
Advanced formulas are used to predict churn for future time frames based on current trends and customer segments. For instance, you can extrapolate from churn rates over the past month, quarter or year to predict how many customers will churn next month. Software with churn analytics capability can make it easier to apply advanced churn calculations.
To illustrate the simplest churn formula (the first formula above), let’s say you had 100 customers at the beginning of the month. Over the course of the month you lost 10 customers. This gives you a churn rate of 10/100, or 10%.
You might be wondering what a typical churn rate is. Is yours too high? The answer is, it all depends. Churn rates vary greatly from industry to industry as widely as they do from company to company. The average churn rate for subscription services, for example, is 6-8%, but you may find that rate to be detrimental to your business. Monitor your rates over time to discover what your ideal rate should be.
The advantage of understanding and tracking customer churn is that you can use churn data to evaluate how well you’re retaining customers. You can then do a churn analysis to figure out why you’re losing customers. This lets you implement churn management strategies in order to prevent customer churn and increase retention.
The Totango Spark platform is designed to help you automate the implementation of customer retention best practices so you can reduce churn, promote repeat business and maximize your revenue. It is important to detect churn early so you can intervene before things go sideways. The Detect Risk SuccessBLOC is specifically designed to help your customer success team recognize customers who may be at risk to churn, allowing your team to be more proactive and reduce churn. Register to see a live demo, or try it free to see how we can help you retain more customers and reduce customer churn.