Customer Churn Analytics: 7 Best Practices

Subscription businesses rely on recurring revenue from their customer base, but what happens if too many customers decide to leave?

When customers cancel their subscriptions, it's referred to as customer churn. Customer churn can devastate your business if you don't know how to manage it.

Here's how you can implement a customer churn analysis system in your business.

What Is Churn Analytics and Why Is It Relevant?

Customer churn (also known as customer attrition rate) is the rate at which customers cancel their subscriptions and leave your business. Customer churn analytics measures your customer churn rate and evaluates how to reduce it.

Reducing customer churn is a crucial part of maintaining a healthy business. If you consistently have customers leaving your business, you'll need to bring in enough new customers during that time to make up for the lost revenue.

In addition to being stressful, bringing in new customers will likely cost more than keeping current customers. Customer acquisition costs are high, and the constant need for new customers decreases your customer's lifetime value.

Using churn analytics allows you to find why customers might be leaving, tweak your business processes to create more loyal customers, and reduce your churn rate for more reliable revenue.

Best Practices for Customer Churn Analytics

The following techniques can help you implement proper churn analytics for your subscription business.

1. Collect the Right Data

Data can help you identify patterns in your business and throughout the customer journey. Some common subscription billing metrics to analyze include:

• Customer churn rate: The percentage of customers who leave your business
• Monthly recurring revenue (MRR) churn: The percentage of MRR lost due to customers who have left
• Customer lifetime value (CLV): The total value of revenue a customer is expected to bring in during their lifetime
• Customer acquisition cost (CAC): The amount of money your business spends to bring in a new customer
• Net promoter score (NPS): Tracks loyalty and satisfaction in regard to a specific product or service using survey results

A full-stack payment platform with user-friendly dashboards can make it easier to track and analyze data. In addition, you might aim to gather qualitative data, such as customer feedback, to pair with your quantitative data and get a better understanding of what the numbers truly mean.

2. Effective Communication and Intervention

Customer engagement is a great indicator of loyalty and satisfaction. Are your customers opening your emails, commenting on your social media posts, and spreading the word about your business to friends and family?

Your marketing and customer service efforts keep you in front of current and potential customers, as well as remind your customers of the value that you bring. While you don't want to overload your customers with messages, you should communicate with them often enough to strengthen your community.

Customer churn analytics can also help you identify at-risk customers who might be getting ready to cancel their subscriptions. In this case, you should have a plan to touch base with these customers, offer personalized deals, help them through onboarding, or at least understand the factors impacting your churn rate.

3. Continuous Monitoring and Optimization

Customer churn analytics isn't a set-it-and-forget-it system. You need to monitor your data continuously. A payment platform with reporting capabilities can be beneficial in keeping track of your key performance indicators. If there are significant changes in churn or customer retention rates, you can be notified early on.

Engaging with your customers throughout the entire customer journey can also make you aware of potential issues or complaints before they become an issue.

You can use all of the information from your data and customers to change business processes as needed. You'll have plenty of chances to optimize your products or services to improve customer loyalty. For example, if you see large amounts of voluntary churn due to poor onboarding, you might change your onboarding process to make it easier for customers.

4. Analyze Customer Behavior Patterns for Early Churn Detection

In addition to other churn metrics, you should also monitor customer behavior patterns. Say you offer a subscription for an online class. You'll need to keep track of how your customers progress through the class to see if there are any particular spots where people quit or cancel.

Identifying how your customers use your product or service can give you a better understanding of why they might decide to leave. The earlier you can detect a customer who is about to churn, the more likely you can take action to keep them around.

5. Use Customer Data for Comprehensive Churn Understanding

Data can tell you a lot about how to make customers happy, and you can use it to reduce your churn rate. You should gather data such as customer demographics, product usage data, customer feedback, billing information, and anything else you can learn about your customers and how they interact with your business.

Understanding your customers on a deeper level will give you actionable insights into how you might introduce new product features, offer subscription levels, market your business, and more. You'll also likely increase customer retention rates due to better customer experiences.

6. Validate and Refine Your Churn Prediction Models

Churn prediction models can combine all of the different types of data mentioned above to help you accurately identify certain customers or segments of customers that might be at risk of churning.

Predicting customer churn starts with looking through historical data to find patterns in churn behavior. AI and machine learning are also generally used to identify customers who might churn, and the algorithms become more accurate over time as the software learns more about your customers' behaviors.

You may need to refine your prediction model as you go. For example, you might try different algorithms, add new software features, or change data parameters to make the model more precise.

7. Segmentation for Targeted Retention

Customer segmentation will split your customers into groups based on specific characteristics, such as demographics or what stage of the customer journey they are currently in. Segmenting your customers improves your ability to communicate and offer value specific to their needs.

After gathering and analyzing your data, you should be able to segment the customers who are more likely to churn into their own group. Then, you can target these customers with specific messages to increase retention rates.

Reduce Customer Churn Rates With a Payment Optimization Platform

Churn analytics and revenue recovery ensure financial success in subscription businesses. While voluntary churn often stems from customer dissatisfaction, it's crucial to address involuntary churn. Research shows that payment failures account for approximately 30% of all churn cases, highlighting the significance of effectively resolving issues with payment processing.

Revolv3 is a full-stack payment platform made specifically for subscription businesses. With more efficient payment processing, your customers are less likely to churn. Learn more about our payment solutions to get started.