Understanding

Customer Churn

Quantify your customer retention

By
Mack Grenfell

For SaaS companies that rely on a subscription business model, customer churn is a crucial metric. It represents the percentage of your customer base that cancels their subscription from one time period to the next.

It's typical to analyse customer churn on a monthly or annual basis, but you can calculate churn over any time period so long as you know the number of customers that you have at the beginning and end of that time period.

How do you calculate customer churn?

The basic formula for calculating customer churn is:

Putting this into words, customer churn for a given period is equal to the number of customers lost over that period divided by the initial customer number at the start of that period.

Note that customer churn doesn't pay any attention to how many customers you've gained in the relevant period. It's simply a consideration of the proportion of your customer base that you lost in any given period.

An example calculation

To let this sink in, let's run through a quick example.

Let's say that your SaaS starts the month with 200 customers. Of those 200 customers, 194 of them are still customers by the end of the month.

Now let's ask, what is your churn rate? We can plug the values above into our earlier equation:

When we do so, we see that our customer churn comes out at 3%, a perfectly reasonable number for a typical SaaS business.

Modelling customer churn in Causal

Causal is an interactive modelling tool, which lets you build fully customisable financial models for your SaaS business.

The below is an example of what a customer churn model might look like in Causal. If you want to get under the hood, and see exactly how the model works, you can also click Use this template in the top right of the model.

While you're here...
If you're looking to build financial models for your SaaS business, you might like our product — Causal. It lets you build fully customisable financial models that integrate with a range of popular data sources. Click here to learn more.