Churn Analytics 101: How To Analyze and Reduce Customer Churn [+ Best Tools]
Churn analytics helps you detect your product friction points and understand why users stop using the tool.
This is crucial if you want to know how healthy your SaaS product is and what should be improved to increase customer retention and lower the churn rate.
After reading this blog post, you’ll learn: how to calculate customer churn, what metrics to track, what tools to use to understand the reasons behind churn, and how to act on the collected churn data.
- Customer churn analytics helps you identify the reasons why your existing customers are leaving the product and impede this.
- An average churn rate of over 10 % indicates trouble. This means you should conduct churn analysis and act on it to improve customer retention.
- Additionally, churn analysis will help you determine if you should focus on customer onboarding or product usability.
- Among the most common roots that lead to customer churn are insufficient onboarding, bad customer support, wrong product expectations, and high pricing.
- For effective customer churn analysis, you can
- Track customer behavior using event-tracking and segment them to identify the disengaged users with characteristics such as inactivity, low NPS score, negative feedback, etc.
- Analyze NPS results to reveal potential churn by looking into detractors and passives’ responses.
- Trigger in-app surveys when users interact with your product or service, or include churn surveys in your cancellation flow to gather qualitative churn insights.
- Monitor changes in usage pattern such as frequency, intensity, or type of product usage to see if customers are leaving or engaging with your product.
- Define important touch points across your customer journey to track how your users make progress and notice if there is friction.
- It’s also important to take action for churn prevention and drive customer retention. You can proactively retain customers by:
- Personalizing the customer experience from the start using data from a welcome survey.
- Triggering in-app messages using automation to reach out to specific segments of users who are exhibiting churn behaviors.
- Studying the navigation paths and interactions of your loyal customers to create happy paths for all users.
- A/B testing to identify positive changes and optimize customer experience across the customer journey.
- There are six essential metrics to keep an eye on when carrying out churn analysis. These include customer churn rate, customer retention rate, customer health score, customer engagement rate, customer satisfaction score, and NPS score.
- You can use Hotjar for heatmaps and Baremetrics, a subscription analytics tool to analyze churn.
- For customer churn behavior analysis, you can use Userpilot with a variety of features such as event tracking, analytics dashboards, surveys, etc. Book a demo to see how!
What is churn analytics?
Churn analytics, also known as customer churn analytics or customer attrition analytics, refers to the process of analyzing and understanding why your existing customers are leaving the product.
The goal of interpreting customer churn data is to pinpoint the factors that lead to attrition so that you can take proactive measures to retain customers and improve customer loyalty.
Why is it important to track churn analytics data?
When it comes to SaaS companies, your monthly customer churn rate shouldn’t be higher than 5-7%. This is a golden middle that indicates your customer’s love for your product, and it helps them get their job done.
But in fact, the customer churn rate sometimes can exceed even 20%, which turns into a make or break for a business. Hence, analyzing customer churn will allow you to detect and eliminate the main pain points in the user journey and provide a better user experience.
More specifically, churn analytics will help you to:
- Improve customer experience: The sooner you perform churn analysis, the quicker you will receive user feedback and uncover what hurts your customers most. As a result, you will improve the overall customer experience across your product and reduce customer churn.
- Identify friction points: As you track user behavior across the customer journey for churn analytics, you can detect critical technical issues, bugs, and friction points that your customers encounter so that you can prioritize and fix them ASAP.
- Optimize the product: A customer churn analysis will give you data to optimize your products, whether your UX was misleading or your onboarding wasn’t up to par.
- Increase customer retention: Taking proactive measures towards preventing churn will help you increase retention and drive growth when you can increase customer lifetime value.
What are the reasons for customer churn?
Here are the most common reasons why customers stop paying for your product, according to the Zopka study:
- Poor onboarding: Long non-personalized product tours and a lack of in-app guidance can confuse users and prompt them to churn when a good in-app onboarding gets customers to the “Aha!” moment in the fastest way possible and decreases the likelihood of customers churning.
- Poor customer service: Excellent and timely customer support is a key to customer satisfaction. Insufficient customer support and a lack of in-app help centers, articles, and other tutorials can cause customers to say goodbye.
- Unfulfilled expectations: When it comes to acquiring new customers, the worst thing you can do is lie to them and set unrealistic expectations. Check your website copy for fluff and make sure your product works as it is described. Also, get your sales team to a mutual understanding regarding this issue.
- High pricing can also result in customer churn and a lost revenue stream. Particularly if your product does not boast a “killer” feature that everyone is willing to pay top dollar for. Try to adjust your pricing line to the market and see if it works.
How to perform customer churn analysis?
Here we will go through methods that help you analyze customer churn and identify reasons why you are losing customers.
Segment customers to identify disengaged users
Customer segmentation is defined as the process of grouping your customers exhibiting similar traits.
This can help you detect the emerging patterns of an untoward but upcoming event such as subscription cancellation.
With Userpilot, you can easily monitor the in-app customer behavior and identify the disengaged and churn users with characteristics such as inactivity, low NPS score, negative feedback, etc.
Analyze NPS results to reveal potential churn
While NPS scores are a reliable measure of how high customer loyalty is, they can also reveal actionable insights into what part of your product experiences friction.
Apart from monitoring your NPS pattern, you can also look at qualitative responses from follow-up questions. Thus, you will find out what made a user give you a low score.
By tagging NPS responses, you will be able to see common issues among passives and detractors, and what made a user give you a low score. Such data can be used to deliver proactive customer support before they churn.
Use micro surveys to determine the reasons behind churn
Micro surveys are used for gathering in-app contextual feedback. By triggering in-app surveys when users interact with your product or service, you will have insights into customer experience and see if they are having positive experience or not. This is helpful to detect early signs of churn, if any.
Apart from that, you can also include surveys in your cancellation flow. It helps you understand why customers churn, if they do while also providing a good friction to delay cancellation.
In your churn survey, you can include a list of possible churn reasons with an open-ended question to uncover issues you might be missing out on.
Monitor user behavior across touch points to find friction
Another way to analyze churn is to monitor user behavior and see if your customers are experiencing friction using funnels.
You can define important touch points across your customer journey, and track how your users make progress.
If there are drop off points, customers may be struggling or there are issues with your product. Then you can cross check with customer behavior with that specific touchpoint to pinpoint the root cause.
Analyze usage pattern to detect at-risk customers
Analyzing usage pattern is a useful way to find at-risk customers. By monitoring changes in usage pattern such as frequency, intensity, or type of product usage, you can tell if customers are leaving or engaging with your product.
For example, you can examine the correlation between the number of unique users and the total count of feature usage overtime. Such data will help you uncover declining engagement rates or a decrease in the diversity of features accessed, which may imply at-risk customers.
How to improve customer retention and reduce churn?
Detecting churn is important but taking measures to address customer issues and improve customer retention is also necessary. Here are the ways that you can reduce customer churn.
Personalize customer experience from the start
Personalizing the customer experience from the very beginning is a strategic method for preventing churn. By implementing a welcome survey during the onboarding process, you can gather valuable customer data regarding their preferences, needs, and expectations.
This data serves as a foundation for tailoring interactions and offerings to match individual tastes, effectively building a strong initial connection.
Trigger in app messages to address customer issues
You save at-risk customers by triggering in-app messages using automation to reach out to specific segments of users who are exhibiting churn behaviors.
By identifying these users and proactively addressing their concerns through targeted messages, you can significantly reduce the likelihood of them churning and reengage these customers.
For example, when certain users display patterns such as decreased engagement, infrequent logins, or a decline in feature usage, you can trigger tooltips to drive feature adoption.
Study loyal customers to create happy paths
Studying the navigation paths and interactions of your loyal customers is also a potent churn prevention method.
By analyzing the behaviors of customers who have consistently engaged with your product, you can extract valuable insights to create optimized “happy paths” for all users, thereby enhancing their experience and reducing churn risks.
You can structure the experience around these paths, you guide new and at-risk users toward the same positive outcomes that your happy customers have achieved.
A/B test to optimize experience across the entire customer journey
Leveraging A/B testing to optimize the entire customer journey is a powerful churn prevention technique. You can either use controlled A/B test or head to head A/B test to identify impactful changes that help customers adopt your product.
- In a controlled A/B test, you can roll out a new experience to 50% of your users while keeping the remaining 50% in a controlled group with nothing showing.
- In a head-to-head A/B test, you can create parallel experiences with the same underlying flows but differing features. For instance, you can provide an interactive walkthrough to 50% of users and tooltips to the other 50%. By analyzing how each group responds, you can compare the effectiveness of these features in helping users make progress and preventing churn.
Important customer churn metrics to track
Now let’s walk through the juicy part of the churn analytics journey and learn what churn metrics you should take care of.
- Customer churn rate: It shows what percentage of paying customers you lose every month.To find out your churn rate, take the number of lost customers over a particular period (a month) and divide it by the number of users at the beginning of that period. Multiply the result by 100.
- Customer retention rate: It works directly opposite and provides you with a percentage of how many customers stay with us from month to month.
- A customer health score is a metric used to understand the likelihood of a particular customer segment to grow, stay consistent, or churn.
- Customer engagement rate analyzes customer behavior and explains how often your users interact with your product and how many product features they engage with during the time period. This data enables you to recognize product onboarding issues and spot shortcomings in the product adoption flow.
- Customer satisfaction score: Discover what features your customers dislike and why.
- NPS score: Gauge the NPS score to identify at-risk customers and try to retain them.
Best tools to collect data for churn analytics
Lastly, we will discuss more tools for churn analysis so that you can choose the best one for your business.
However, it’s better to combine at least two products since they are supposed to complement each other.
Userpilot for in-app user behavior and microsurveys
With event tracking, for both no-code and server-side events, you can monitor users’ behavior inside the app such as what features they are using, when they signed up, how many web sessions they had, etc.
Apart from that, advanced analytics dashboards will provide you with actionable insights such as where your users drop off, what feature has decreased usage, who is struggling, etc.
Such behavioral reporting will highlight problem areas of customer engagement for you to take action and reduce customer churn.
You can also create code-free in-app micro surveys to collect and analyze customer feedback. Advanced targeting and triggering settings will help you assign your survey to a specific URL or domain, button, or feature.
Hotjar for session recordings and heatmaps
This product is excellent for tracking how customers engage with your website in real-time.
It measures how many clicks were done on specific site elements, showing you the most enticing marketing messages or the most used product features.
Also, it can be applied to product analytics. When watching session recordings, you can catch the moment with “rage clicking.” It signifies the user was dealing with a bug or poor UX.
Baremetrics for subscription analytics
Using Baremetrics, you can analyze churn in two categories — ones who were paying you but canceled subscriptions and those who didn’t pay and stopped engaging with your product.
Canceled customers provide a reason for opting out. Possibly unpaid customers forgot to pay or update their credit card information. Before you decide what to fix, you need to know what you’re dealing with.
Thoroughly performed, churn analysis is the one and only way to understand why users drop off. Hence, you can decrease the customer attrition rate and boost your company’s growth.
Want to get valuable insights into churn analytics? Don’t put it on hold! Get a Userpilot Demo and see how you can prevent impending customer churn.