Churn Analytics 101: How To Analyze Customer Churn [+Best Tools Included]
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.
Let’s begin!
TL;DR
- Customer churn analytics helps you identify the reasons why your existing customers are leaving the product and impede this. Meanwhile, churn prediction forecasts the likelihood of customer attrition.
- A churn rate 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.
- 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.
- Among the most common roots that lead to customer churn are insufficient onboarding, bad customer support, wrong product expectations, and high pricing.
- There are three methods to predict churn. The first two are a timely analysis of customers’ engagement and satisfaction. The third one is monitoring a low NPS score and revealing the detractors.
- Using Userpilot, you can easily find NPS detractors and detect disengaged users to reach out to them before they churn.
- It is impossible to catch every leaving customer, so instead, you can use Userpilot’s churn surveys to learn why customers are churning. Then you can utilize the insights to reduce churn.
- You can also use Hotjar for heatmaps and Baremetrics, a subscription analytics tool to analyze churn.
What is churn analytics?
Churn analytics is the data that helps you identify the reasons why your existing customers are leaving the product.
Among the most common reasons for customer churn are poor customer service, a complicated UX, and limited product features.
Once you collect data from churn analytics, you will get crystal-clear insights into what causes customer attrition and how to prevent this.
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.
Now let’s dig deeper and determine what aspects of the product customer churn analytics affect.
Improve customer experience
Literally, anything can cause customers to churn at any stage of their journey. Maybe they lack product knowledge and quit using your product after a month. Additionally, your competitors’ pricing factors may affect their decision to leave you.
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
What if you discover that two specific bugs are the reason why you are losing customers? What a pity! Both of them could have been easily solved if you received feedback before customers churned.
Customer churn analysis will directly point out the critical technical issues, bugs, and friction points that your customers encounter so that you can prioritize and fix them ASAP.
Optimize the product
Customers may drop off due to too many annoying minor bugs or product imperfections, which eventually have a compounding effect. A customer churn analysis will tell you whether your UX was misleading or your onboarding wasn’t up to par. This way you can proactively act on it and optimize your product for a better customer experience.
Increase customer retention
As soon as you determine why your customers were churning, you should strive to solve all of these issues to retain them. Why? Increasing your recurring monthly revenue is the only way to ensure your product thrives and stays profitable.
What metrics should you track for churn analytics?
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.
Let’s apply this formula to numbers. (121 lost customers / 1541 paid customers) x 100 = 7.85% (the churn rate). This means you’re doing pretty well but still can work on lowering monthly churn.
- 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.
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.
- Lack of customer support: 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.
Churn analytics vs churn prediction: Are they the same?
Despite it sounding very similar, both terms mean entirely different things.
Churn prediction is an analysis of historical data (based on churn analytics) and modeling of the churn rate for the following months. It’s usually applied to specific user cohorts.
On the other hand, churn analytics displays past and present numbers of lost customers and identifies the reasons for churn. This allows you to target issues that need to be resolved.
Can you predict churn?
The short answer is yes, you can. But let’s figure out how to do so.
In a nutshell, you can use a product analytics tool to segment your customers and monitor their behavior (product engagement) in real-time. If they are passive or don’t use the product at all, these are potential red flags.
By seeing such user behavior patterns, you can predict which clients are most likely to cancel a subscription.
The next indicator when users are about to go is a low NPS score. If you identify detractors through NPS surveys, you can proactively reach out to them and fix the issue before it’s too late.
3 ways to collect data for churn analytics
Here we will go through three ways that Userpilot can help you collect data to prevent churn. Ready to dive in?
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 users.
To do so, create your own filter of “Highly disengaged” customers in People→Users. Select conditions that define inactive users. For example, the last visit was more than 7 days ago.
Once you identify disengaged users, you can proactively reach out to them to understand why they are not using the app and offer help if needed.
Find NPS detractors and act before they 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.
First, you need to create an NPS survey and add the qualitative follow-up question. Thus, you will find out what made a user give you a low score.
Next, you should go through the answers and apply tags to negative/positive phrases customers mentioned in feedback. From now, Userpilot will automatically recognize these words and bond them with a given NPS score.
Use this data to reach out to detractors before they churn.
Use micro surveys to determine the reasons behind churn
Micro surveys are used for gathering in-app contextual feedback. You can use Userpilot to create an in-app survey and set a certain trigger when popping it up.
This allows you to collect customer feedback on specific features or events like canceling a subscription.
Build churn surveys to find out why users are leaving. Make it mandatory to complete, so you can act on the feedback and improve your product. You may also try contacting the customers to retain them.
What questions should you answer after churn analysis?
Once you completed the customer churn analysis, you get the raw data to analyze and actually work on it.
These questions will help you understand churn metrics and design retention strategies.
What is our current customer churn rate? Are the numbers you have got good or bad compared to benchmarks for SaaS products? What customer segments show the highest churn rate? Answer these, and you define where the problem lies.
Which customers are at high risk of churning? Grouping customers into segments will show you the customers that are most likely to churn. Who they are?
What are the main causes of customer churn? You should find the clue by reading through micro survey feedback and analyzing the NPS scores of particular at-risk segments.
What are the drop-off points? The data you collected should help you to identify the moments when churn occurs. But if you want to dig deeper, we recommend performing the funnel analysis. It will illustrate what concrete steps of the user flow force customers to quit.
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 micro surveys
With advanced segmentation, you can monitor users’ behavior inside the app. What features they are using, when they signed up, how many web sessions they had, etc.
Such behavioral reporting will highlight problem areas of customer engagement. Fix it to 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.
Conclusion
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.
