## Calculate Churn - SaaS Edition

Churn. If you’ve been around a software as a service (SaaS) company, service, or retail company you’ve probably heard of it. But how do you calculate it? Needless to say, it depends on the business you’re operating.

In this post, we’ll start with SaaS churn and in later posts we’ll move to other businesses such as retail. If you’re in retail this post will still be helpful as SaaS churn is one of the easier methods of calculating and understanding churn so it will provide a good foundation for when we talk about the more complex retail churn.

## SaaS Churn

SaaS churn is the percentage of customers who cancel their subscription during a time period.

Mathematically, it’s defined as:

$$\frac{\Delta C}{\Delta t}$$

Where $\Delta C$ is the change in customers and $\Delta t$ is the change in time. $\Delta C$ can be calcuated as $C_start - C_end$.

The change in time is very interesting and sets the standard for the rest of the calculation. If you set it too short, you’ll see no or low churn, whereas if you set it too long you’ll see very high churn with no insight.

Setting the time period relies heavily depends on your subscription model and renewal cycles. If you’re Spotify with a monthly subscription model you may want to choose something like 30 day or 60 day churn, as this will capture the customers renewal patterns for the firsts and second billing cycle.

Where on the other end, Oracle with multi-year deals may not deal with churn explicitly as we know it. But they still account for it the in the Renewal rate of these longer term contracts – a similar metric but just ignores the time component and figures if a customer simply renews or not.

Further more, the time component may dictate over what scope you’re measuring churn. For example, 90 day churn could mean you observe churn for all customers over 90 days or you could narrow your focus and look at customers in their first 90 days as an indication of onboarding.

### The effect of churn.

Churn is inevitable. Ultimately at some stage your customers will leave whether they go out of business, lose interest, or dear I say it – die. Churn is all about managing the rate of which customer Churn.

To understand the effect of churn, take a look at the following graph and play around with different churn values to understand how different churn rates effect this:

## What is an acceptable churn rate?

Answering this question is akin to answering how long is a piece of string. Luckily though, we do have some guidance.

SaaS Tomasz Tunguz suggest a revenue churn rate of 10% is acceptable, this corresponds to a monthly churn rate of 0.87%.

In reality, I’d say a good churn rate is one in which it is improving. But there are some general factors that can affect churn, such as:

• Billing cycles. Do you auto-charge customers? Is your billing cycle too long or short?
• Product substitutes. Is your product useful for short periods of time, eg Summer sport providers? Are your competitors price and feature matching to you?
• Customer support. When issues arise are you able to triage them in a timely and

Of course, there are economic and societal factors which not only affect churn but affect your overall business strategy.

## Churn Deviations

Using the same methodology, SaaS businesses may derive two extensions to this:

• User Level Churn
• Subscription/Revenue Churn

User Level churn is likely what you’re already calculating unless the SaaS company is B2B in which case there’ll likely be a notion of Users and Teams/Organizations.

Revenue Churn should always be monitored as it indicates the business’ ability to upsell or at the very least prevent downgrading.

In future posts, well break down these two deviations as they are useful for a well rounded churn strategy.