The Guide to Customer Churn Analysis

Churn is customers leaving your business. And for any SaaS company, understanding what churn is and how to analyze it is a core pillar for building a successful subscription business, whether it's SaaS, e-commerce, or a general subscription model.
Beecause just a 5% reduction in customer churn could increase profits by anywhere from 25% to 125%. That’s why it’s so important for the long-term health of your SaaS business to conduct regular customer churn analysis.
Why customer churn analysis matters
What is customer churn analysis?
Customer churn analysis is the evaluation and examination of your customer churn rates, with the goal to reduce or minimize your business' overall churn.
Your churn rate is the percentage of your customer base that you lose within a given time period. By analyzing that churn rate, you can gain valuable insights into why your customers cancel. And by performing a churn analysis, you can figure out how to fix the problems that cause customers to churn.
Why does customer churn analysis matter?
Think of it like this: when you acquire new customers, you’re inviting them in through the front door. A front door that you likely spend a lot of resources to make big and inviting. But, with all of the focus on that front door, you may forget to tightly close the back door. And when you have people slipping out the back door, it makes the numbers that you’re bringing in for the first time less significant.
There are many reasons why the back door may end up cracked open in your SaaS business. The causes of churn are numerous and different for every company. The important thing is to figure out why your business specifically is losing customers.
Customer churn analysis is the number one way for you to evaluate why people sneak out the back — and, most importantly, what you can do to close it.
How will churn analysis affect my business?
You don’t have to have extremely high customer churn rates in order to benefit from a thorough customer churn analysis. In fact, it’s important to analyze your customer churn frequently and accurately if you want to improve or maintain the health of your business. Regardless of your churn rates, customer churn analysis can help empower you to make better overall decisions in your business.
Churn compounds over time. The longer you leave churn unchecked, the more painful it's going to be for your business, even if your churn is in the single digits.

See how churn rates compound over time? This is why churn analysis is essential.
Churn analysis can help you better support customers
Finding ways to support your customers at key moments in their journey is vital to improving growth and retention. If you see a pattern of customers dropping out at specific moments in their customer journey, customer churn analysis can help you examine why that pattern is occurring and how you can fix the underlying issue.
Churn analysis can help you lower CAC and increase revenue
Customer acquisition cost, or CAC, refers to the total cost of sales and marketing that’s required to acquire a new customer. And CAC eats away at your company’s revenue. Why? Because acquiring new customers will always be more expensive than maintaining and upgrading your current customers.
When you conduct effective customer churn analysis, you can lower your churn rates, which, in turn, lowers your CAC, and increases your overall revenue.
Churn analysis can help you refine your product
When you analyze the different types of customer churn your business is facing, you can gain insight on ways to improve or refine your products so they can meet customer needs more effectively. And by providing more value to your users and eliminating the things that frustrate them, you can reduce your customer churn.
How should you analyze your churn data?
If you want to conduct a truly effective customer churn analysis, then you have to know which metrics and key performance indicators to track and analyze over time. Let’s talk about a few of the metrics that most influence your customer churn rate.
Customer engagement and product usage
One metric that can predict or indicate an issue with churn is a decreasing customer usage rate. By keeping an eye on how long your customers use your service before displaying signs of declining usage rate, you can begin to identify at-risk customers earlier.
You should also track customer engagement and use that as an indicator for potential churn. For instance, if a customer is using your product less and less from month to month, then there’s a much higher likelihood that they’re going to cancel. If you can identify lower customer engagement during your customer churn analysis, then you have a chance to target them before they hit the cancel button.
Customer behavior and preferences
No matter what type of product or service you offer in your SaaS business, odds are you’re serving more than one type of customer. And because you have different types of customers with different needs, it’s important to analyze the behavior, patters, and preferences of these various groups.
During customer churn analysis, it’s vital to sort and filter your various customer types based on similarities in behavior. That’s where cohort analysis comes in. Cohorts are customers sharing common traits and characteristics. In cohort analysis, you’ll study how these cohorts change over time, throughout the customer lifecycle.
You can use cohort analysis to isolate customer behaviors and identify patterns. Cohort analysis is useful for determining which customers are at a higher risk for churn, which customers are more likely to disengage after a certain time, which features of your product are underutilized and most utilized, etc.
Customer segmentation
During a customer churn analysis, it can be helpful to group users that have similar traits in order to identify trends. This process is known as customer segmentation. Customer segmentation can help you observe whether churn risk differs depending on how long customers have been using your product, how incentives (like discounts, offers, etc.) affect churn rates, etc.