7 Strategies for Predicting Customer Churn

Customer churn is expected in any subscription business model. Over time, your customers will cancel services for various reasons. As a subscription business owner, it's important to do more than track customer churn. You must attempt to predict it.

Here's why predicting customer churn is so important and seven strategies you can use.

Why Is Predicting Churn Important?

Churn prediction is important for several reasons. Some of the most pressing include:

• Inventory Management: In order to provide products or services to your customers, you'll need to manage your inventory properly. However, overstocking inventory can quickly become wasteful. When you track and predict customer churn, you have more data for inventory management.
• Retention Opportunity: Churn prediction requires knowledge of churn risk actions or actions that lead to customer churn. This allows you to attempt to retain your customers before they cancel, a valuable opportunity since customer retention is typically less expensive than customer acquisition.
• Better Financial Forecasting: Predicting customer churn gives you improved data for financial forecasting. This leads to improved budgets and more educated decisions surrounding advertising and other spending categories.

7 Ways To Predict Customer Churn

If you're unsure how to start predicting customer churn, follow the approach below, and you'll be on the right track.

1. Collect and Analyze Relevant Customer Data

As with any prediction concept, you'll need to gather data for customer churn prediction. Some data points to look for include:

• Customer Lifetime: How long does your average customer stay on the books? Avoidable failed payments lead to about 50% of all customer churn, depending on specific industries, businesses, and other factors.
• Product or Service Usage: Do your customers typically stop using your product or service before they decide to cancel?
• Risk Actions: What actions do your customers usually take before they cancel their subscriptions?

The more relevant data you collect, the more accurate your churn analysis will be. So, brainstorm the specific data points that you believe are key factors to customer cancellations in your business and analyze those data points.

2. Measure Changes in Churn Rates and Other Churn Indicators

Keep track of the relevant data you're collecting and analyze it weekly, monthly, or quarterly. This analysis ensures your customer churn predictions are up-to-date based on current data.

But that's not the only benefit of regularly tracking customer churn rates and indicators. As you measure changes in these indicators, you'll see where your business is lacking and doing well. This gives you the opportunity to optimize your processes and reduce customer churn.

3. Segment Your Customer Base

All customers are unique, but many of them share similar qualities. An understanding of those similar qualities offers you in-depth data that can help you better predict customer churn.

For example, you may find that your female customers ages 35 through 55 are your most loyal customers, while those outside this demographic are high-risk customers. Understanding the difference between the two and the percentage of your audience they represent sets the stage for more accurate churn predictions.

It can also help you reduce your customer churn rate by focusing your advertising dollars on an audience that likely has future loyal customers.

4. Build a Customer Churn Prediction Model With Machine Learning

As technological innovation continues, advanced tools bring more accuracy to the customer churn process. Today, you can use machine learning to develop a churn model focused on unlimited target variables.

This churn modeling uses machine learning and logistic regression to tell you how likely customers are to churn. The most common form of machine learning for this type of modeling is known as random forest modeling. This involves processing data sources and then learning and adjusting the model.

However, it's important to use a quality machine prediction learning model. Some prediction models only focus on those who are likely to cancel immediately and those that aren't, a form of binary classification. The best models use long-term data to make accurate customer churn predictions rather than immediate values.

5. Monitor Customer Behavior

As you continue to improve your customer churn prediction process, it's important that you monitor your active customers. Changes in demographics or how your customers use your product could change customer churn rates.

Moreover, as you monitor customer behavior, you'll likely find opportunities to improve your product or service. This can increase customer retention rates, further growing your business.  

6. Analyze Customer Service Interactions

One of the most common reasons for customer churn in subscription services is the customer feeling they didn't receive quality customer service. Customers feel as if they can't speak to someone knowledgeable enough about the product or simply don't get the answers they want. Monitoring your customer interactions will help ensure your customers get the highest quality of services possible. You'll likely find areas of your service that are a common source of customer complaints or identify features they like the most.

Monitoring these interactions doesn't just help you improve your churn prediction process; it can help you keep more customers on the books for longer by improving your service.

7. Conduct Regular Surveys To Gather Feedback

Your customers may cancel for a wide variety of reasons. If you never ask them what they like and dislike about your service, you'll never get the full picture. That's why it's important to conduct regular surveys and pay close attention to the feedback you receive.

Start by asking the basic questions your data says are essential. At the end of each survey, give your customers the opportunity to write a unique message with other thoughts they might want to share.

You can use this feedback to determine what aspects of your service cause customers to cancel and address those issues to improve customer retention.

Decrease Your Risk of Churn With Cutting-Edge Technology Solutions

As you build your customer churn prediction models, it's wise to work on churn prevention. Many subscription services find that one of the leading causes of customer churn is declined transactions. That's where Revolv3 comes in.

Revolv3 isn't just a subscription payment solution. It's the first one that focuses on reducing involuntary churn by improving approval rates. With Revolv3, you'll never pay for declined transactions, and you'll enjoy higher approval rates thanks to dynamic routing. Schedule your demo to learn the Revolv3 difference today.