Analyzing Churn Data

If you’ve already gone through Identifying Churn, then you know the basics of recognizing when a customer might be on their way out. You might still be wondering, “What do I do next?” or “Now what?” Good questions. Now it’s time to dig into the customer health data and uncover why customers are leaving. Going beyond churn data isn’t just about looking at who’s leaving—it’s about understanding the patterns and trends that can help you stop churn in its tracks. Let’s break this down into simple steps.

Segmenting Customers: Who’s at Risk?

Not all customers are created equal, and neither is their risk of churning. This is where segmentation comes into play. By dividing your customer base into groups—like high-risk and low-risk—you can target your efforts where they’ll have the most impact.

High-Risk Customers: Customers with declining health scores or reduced activity often fall into this category. They need immediate attention to uncover their challenges and provide solutions.

Low-Risk Customers: These are your satisfied customers with consistently high health scores. While they may not need immediate intervention, you can use insights from their behavior to replicate success in other segments.

Demographics and Psychographics: The Human Side of Churn

Understanding the demographics and psychographics of your customers can give you great insights into why they might churn. These two words might not seem like much, but together, they help you understand your customers better.

• Demographics cover the basics—age, gender, income, and location.

• Psychographics delve deeper into their values, attitudes, and lifestyles.

For example:

• Younger Customers might churn if they perceive your product as outdated.

• Higher-Income Customers might churn if they feel the product doesn’t offer premium value or a high-end user experience.

By understanding these factors, you can tailor your product and messaging to fit the needs of different customer groups.

Using Customer Health Data for Churn Analysis

Customer health data is your gateway to insights that go beyond basic segmentation and demographics. This data helps you understand how customers are engaging with your product, which features they value, and where potential issues might lie.

Key areas to monitor include:

1. Log-in Frequency: Declining log-ins often signal waning interest.

2. Feature Adoption: Are customers exploring and using your core features?

3. Session Duration: Shorter sessions might indicate dissatisfaction.

4. Support Requests: An uptick in support requests could reveal unmet expectations.

5. Community Participation: Engaged customers often participate in community forums or other social aspects of your product.

By analyzing these areas, you can create a clear picture of where customers are thriving and where they’re struggling.

Calculation and Benchmarking: How Do You Stack Up?

Knowing your churn rate is critical, but it’s really just the start. You also need to benchmark it against industry standards or your own historical data to understand what it really means.

For instance, if the industry average churn rate is 3%, and yours is at 7%, that’s a sign you need to dig deeper into the customer health data and figure out exactly what’s going wrong.

The Bottom Line: Information is Your Best Defense Against Churn

Churn isn’t just a number—it’s a mystery story. And, in a sense, you’re the detective trying to solve that mystery. By going through churn data, segmenting customers, and understanding the demographics, psychographics, and customer health scores, you can uncover the root causes of churn. This knowledge enables you to turn the tide in your favor. As the old phrase goes: “Knowledge is power.” It certainly applies here.