3-Step Churn Analysis Model: What Works and What Doesn’t

If you're looking to keep your customers coming back, this churn analysis model is for you. Learn what works and what doesn't in preventing customer churn.

When it comes to customer churn, every business wants to know how to keep their customers coming back. That’s where the churn analysis model comes in. This model can help you identify what works and what doesn’t in preventing customer churn. So if you’re looking for ways to keep your customers happy and loyal, read on for more insights from this valuable tool.

What is a Churn Analysis Model?

A churn analysis model is used to predict whether a customer is likely to stop using a company’s products or services. The model is based on a variety of factors, including customer satisfaction, customer service interactions, and product usage.

What is Customer Churn Analysis?

Churn analysis is the process of understanding why your customers have stopped using your product or service. This understanding can be gleaned through data analysis to help improve future customer retention.

By analyzing your churn rate, you can identify potential areas of improvement to keep more customers engaged with your business.

Over the last six months, your rate of customer attrition has skyrocketed from 4% to over 10%.

You sit there, confused, and wondering what happened.

At this stage, many business owners make drastic, desperate changes to their business to try and stop the bleed.

Or, you can analyze your failed sales attempts by doing some “churn” analysis on your sales data.

In this guide, we’ll show you how to use a few simple steps to figure out your churn rate.

Churn analysis is the process where you identify which of your customers have stopped using your service, why they’ve stopped using it, and how to prevent it in the future. To do this, you need to identify which of your customer have canceled, and then contact those customers and ask why they stopped using the app.

Why You Need to Analyze Churn

It’s helpful to know you have a 13% customer attrition, but without knowing why they’re leaving, when, and other data, it’s hard to improve.

Churn rate is an important metric for subscription services, which is why it’s important to analyze it.

Sometimes, a SaaS business will realize that they have an issue with retaining customers, but they don’t know how to go about fixing it. So, they either make assumptions about what the problem is, or they use random strategies they found on the internet.

The issue with this is unless you know why your user is leaving, any change you make may worsen the situation.

If you’re currently experiencing a high amount of customer turnover, then you shouldn’t change your prices, features, or process without analyzing your reasons for doing so. Instead, you should first figure out why your customers are leaving so that you can take steps to reduce it.

If you want to keep your customers from churning, you first need to take the time to analyze why they’re leaving. Only then can you make controlled changes and tests to see what impact those changes have.

When to Conduct a Churn Analysis

Most folks don’t decide, “Hey, I think I’ll analyze my customer attrition rates!” out of the blue.

Analyzing your churn is usually triggered by an event.

If you notice your subscriber retention rate decreasing, or if it is steadily declining, this could be a sign that something is wrong. Investigate your data to find out the cause of the problem, and take steps to prevent it from getting worse.

Those are signs that something is up, and you’ll need to look into the data to figure out why.

The trigger doesn’t have to be a negative one. For instance, maybe you’ve been running a marketing campaign to onboard new subscribers to your product or service, and you want to see how it’s impacted your retention rate.

That, too, is churn.

As a general rule, it is advisable to conduct churn analysis whenever an unusual event (positive or negative) occurs, or when a change is made that could potentially affect churn rates. By doing so, you can stay on top of any potential problems and make necessary changes to prevent them from happening.

How to Do Churn Analysis in 3 Simple Steps

As a marketing professional, I often have to look at a lot of data. But, it can be a lot to process at times.

So, I find that it’s best for me to create an outline before I start, rather than diving in and experimenting.

Before anything else, you need to identify what problem you are solving.

In this case, we need to understand which customers are churning and why so we have context and direction for how we will evaluate the data. That’ll help us avoid going down a rabbit hole of endless data.

Now that we’ve covered what we are looking for, let’s get into how to actually do it.

Step 1: Setup Churn Analytics Tools

Before you can do any analysis on your client base, you need to have data to do so!

There are a bunch of different tools available, but we’ll keep it simple for now.

For tracking your subscribers, you’ll need a subscription analytics platform.

You can gain all of the insight you need from one place.

Product analytics tools such as Mixpanel and Amplitude can be a huge help when analyzing how customers engage with your product. They help you see what features of your app are used the most, and which are rarely or never used. 

Tracking product usage and engagement with your product can be a great way to identify customers at risk of churning.

Don’t get too caught up on the tools. Start with the basics, and if you aren’t getting the response you need, then branch out.

Step 2. Find Out Why Customers Are Churning

One of our two objectives is to find out why people are canceling.

To answer your questions, first, you have to ask! There are several ways you can do this.

Some SaaS companies have resorted to just sending out an email after a customer cancels.

They’ll either ask you why you canceled in the email or direct you to a type form made from Google Docs.

Here’s an example of how one company uses email to get feedback from customers that canceled.

churn analysis model (Source)

Concise, to the point, and easy to understand.

This tactic works pretty well for early-stage startups, but as you grow, you’ll want to find a better way to understand why customers churn.

Another option is to send out a questionnaire to customers before they cancel their accounts. This gives you valuable insight into why they’re canceling so that you can improve our products and services.

This will look like this:

churn analysis model (Source)

The form can capture all the information you need and you can keep track of all responses in your CRM.

Let customers tell you why they’re canceling their subscriptions. This helps you improve your service and prevent further cancelations.

You can figure out which customers are likely to cancel their service based on this information.

What is the most common reason for customers churning? How much revenue are you losing to each customer who leaves?

For cancelations due to price, you’ll have to do more research.

But looking at it this way, you can better decide where to focus your efforts.

If customers switch to a competitor’s product or service, note which competitor they are switching to. This can help you figure out how your offering compares to the competition.

Then, use a tool like Crayon to create a product-feature-comparison-matrix like the one below. This will show you where your products fall short, and what you can do to improve them.

churn analysis model (Source)

If the price seems to be a common reason for cancellations, you may want to run some experiments. This can help you determine whether dropping your rates is the right solution.

A word of warning: If customers consistently cancel because of cost, that doesn’t necessarily mean you should lower your prices. Instead, you may need to offer more value to current and potential customers, or the customers who were canceling may have needed a different package.

It’s possible that your prices are too high, or that your customers are on the incorrect plans. It’s important to find out why customers cancel before changing your prices.

People may cancel your subscription if they feel your prices are too high. Before assuming that your prices may be too expensive, consider the value of your product.

A 1:1 price-to-value ratio is good, but the customer may feel that they aren’t receiving enough value for what they’re paying.

With a 10:1 value-to-price ratio, your customers will feel so compelled to spread the word about your company and stay with you for a long time.

We ran an experiment in which we increased our prices for our services. We hypothesized that customers would balk at the price increase, but we saw almost no change in their behavior. This tells us that our prices are, in fact, not too high.

A lot of our customers were reluctant to upgrade to our $100 per month package from the $50 a month one.

We often receive feedback from users who try our product but don’t convert that they can’t justify the $100 price point.

We introduced our new $75/month plan and haven’t seen any customers leave. In fact, many have been upgrading with no complaints.

Another thing to consider is the type of customer you’re losing to cancellations. Are they just canceling, or are they just not paying you?

Expired or canceled customers are those who have decided to no longer use your product or service. This could be due to a variety of reasons, such as deciding that the product was no longer a good fit or forgetting to pay their credit card.

Before deciding what needs to be fixed, it is important to first understand the current situation.

Step 3. Analyze Churn by Cohorts

Imagine that you are a software company that recently lost 300 customers.

Those 300 customers are on different plans, signed up at different times, in different countries.

Would you rather analyze all 300 of your customers at once, or would you rather break them into groups based on their level of membership, when they subscribed, and their location?

Analyzing the data from the first method of tracking may reveal some trends.

But to truly gain insights into why your customers are churning, it’s much more effective to segment your lost customers and study them individually. This will help you understand exactly why they’re leaving you and what you can do to prevent them from doing so again in the future.

Start with the plan level and the subscriber’s date of signup.

Let’s take a look at an example of how to do a churn analysis for pricing tiers.

Once you’ve identified which plans have the highest churn, you’ll want to figure out why those users are leaving. We’re using a simple spreadsheet for this.

In the Excel file, you can filter the rows by Plan, and see all the cancellations under that plan for that user. You can also read the comment for each canceller in the Excel spreadsheet, which may give you further insight into why that customer canceled.

Looking at your retention by cohort can help you understand if your customers are signing up and sticking around.

Using this data, you can compare the trends of when customers sign up and when they decide to cancel.

It would be interesting to see if there are differences between customers that joined 3 months ago and 6 months. So the next step is to compare the 3-month cohort to the 6-month one.

You want to see if there’s any correlation between ARPU and the two cohorts.

This will allow you to calculate the value of each customer in each cohort.

The takeaways from this short churn analysis showed that we have a better chance of keeping customers who sign up for or upgrade to advanced plans.


A churn analysis model is a valuable tool for any business looking to keep their customers coming back. By understanding what works and what doesn’t in preventing customer churn, you can take steps to ensure your customers are happy and loyal. So if you’re concerned about customer retention, be sure to give this model a try.


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