How to Predict Customer Churn (With Expert Advice)

Customer churn is a natural part of the SaaS sales cycle. And because retaining customers is less costly than finding new ones, businesses need to find ways to manage and reduce customer churn. One of the best ways to do that is to identify the factors that lead customers down the path to non-renewal.

In this post, we’ll look at how to predict customer churn and strategies for preventing it. Then we’ll share insights from SaaS leaders about their experience with predicting customer churn.   

What Is Customer Churn?

Customer churn is calculated as a percentage — it’s the number of customers lost during a specific period, divided by the number of customers at the beginning of that period. So, if you had 1,000 subscribers at the beginning of Q1 and lost 30 of them in that quarter, your churn rate would be 3%.

What Is Churn Prediction?

Churn prediction is determining which customers are likely to churn, based on historical data and their usage of the software. For example, let’s say that based on your CRM data, you know that customers you’ve lost in the past were those who rarely used several key elements of your software. That tells you that any current customers who aren’t fully using your software might decide to not renew their subscription. 

What Causes Customer Churn? 

Sometimes, churn may be a result of factors beyond your customer’s control, such as the hiring of a new manager with different priorities, or an unforeseen budget cut. Generally, though, these are the three most common reasons customers churn:

Perceived ROI

This is a common theme — that the cost of the software outweighs its benefits. This perception may arise when a SaaS product is useful for a certain team, but not an entire organization. Or it may stem from a lack of reporting features that could prove the software’s value to management. 

Low Adoption

Busy teams may not have much time for onboarding, and if your company doesn’t offer assistance during implementation, your customers might not be able to fully engage with your product. 

Low adoption may also occur when your customers’ priorities change. For example, they might’ve purchased a software solution for managing content production but stopped using it when they began outsourcing content. 

Poor Integration

Businesses buy software to make their jobs easier, but if a SaaS product doesn’t integrate with the tools they already use, their workflows can become much more complicated. 

Customer Service

Even though most communication between SaaS providers and their customers is digital, customers still want the ability to speak to a human being, should they need assistance. A dedicated customer success representative or a support desk that offers live chat could help improve customer satisfaction and reduce churn. 

Metrics to Help Analyze and Predict Customer Churn

So, data can help you understand and predict customer churn, but what metrics should you be reviewing? These are the key metrics to watch:

Usage Baseline

To know when a customer’s usage of your product is below average, you need to establish a usage baseline that incorporates the following metrics

• Activation Rate

“Activation” means that your customer has achieved the desired outcome using your product — for example, sunsetting an old platform and using yours to manage all digital marketing assets. 

Activation Rate = Activated Users / Acquired Users

• Feature Adoption

Your feature adoption rate can be calculated in several ways. You might want to look at what percentage of your customers use all of your product’s primary features so you can identify any correlations between feature usage and churn. Or, you could look at which features customers tend to use when they first acquire your product and see if usage of those features declines over time. 

• Retention Rate

Your retention rate is the inverse of your churn rate — so, if your churn rate is 5%, your retention rate is 95%. Review this metric regularly to see if it changes over time. 

Baseline Churn Formula

To get an accurate picture of your churn rate, you’ll need to collect data for two months. Here’s the baseline churn formula:

(# of Customers on Month 1, Day 1 + # of Churned Customers on Month 2, Day 1) / Total Customers in Month 1

Historical Trends

Review your customer data and look for trends. What do your former customers have in common? Were churn rates higher for customers with the lowest service tiers? Did business size have any impact on customer churn? Answering these questions will help you identify your current customers that are a churn risk.

Also be aware of telltale signs that a customer is about to churn. For example, you may notice that your former customers exported data and moved other files out of your platform before they churned.

Strategies for Preventing Customer Churn

There are a few ways to prevent customer churn, and they all involve increasing the frequency and quality of communication with your customers.  

Schedule Monthly Consultations

Regular interaction with your company can help build customer loyalty. A standing monthly meeting — even if that’s a Zoom call — gives customers an opportunity to ask questions, request new features, and tell you how they’re feeling about your product. 

Prioritize Feature Requests

A feature request is a form of feedback — it means your software is missing some functionality that a customer wants. Ideally, you should segment your customers into groups, based on their feature requests, acknowledge their requests, and provide frequent status updates. When and if you do roll out the requested feature, the users who requested it should be the first to know.  

Use Micro-Surveys

Micro-surveys help you collect important, ongoing feedback without encroaching on your customers’ time. These are the most common micro-surveys: 

• NPS Surveys — Net promoter score (NPS) surveys are ratings-based and usually ask customers how likely they are to recommend a product. Because these surveys require almost no effort from customers, you’re likely to have a good response rate that can help you determine overall customer sentiment.
• In-App Surveys — If you have a lot of mobile users, in-app surveys are ideal for collecting quick feedback. These usually contain just one or two questions, with a limited selection of answers that users can click to register a response.
• Email Surveys — NPS and in-app surveys are helpful for collecting feedback from everyday users, but email surveys might be a better option when looking for “big-picture” feedback from decision makers. For example, a marketing manager might not have much feedback about using your product, but they should be able to answer any questions about overall adoption, perceived ROI, and productivity gains. Email surveys can help you gather this type of information.

What the Experts Said

SaaS is a competitive marketplace, and customers usually have multiple options, when searching for software. Understanding customer churn is the key to retaining customers — and you don’t need to be a data scientist to do that. 

Parlor’s Voice of the User software analyzes user intent and engagement, and provides a single interface for managing all customer feedback. It gives you the data you need to predict — and prevent — churn. 

What the SaaS Experts Said

Now, let’s see what our SaaS experts told us about predicting customer churn!