Here’s why performing a customer churn analysis is so important and how to plan and execute your own.
October 18, 2021
One of the most important — and potentially daunting — metrics for SaaS businesses is churn. Customer churn, otherwise known as customer attrition, is a key performance indicator (KPI) that measures the number of customers who cancel their subscription with your company.
Though the definition of churn seems simple enough, analyzing why your churn is what it is — and fixing it — is more complex. For the average SaaS business, the benchmark for churn rate is around 5% and a good churn rate is considered 3% or lower, according to ProfitWell. Even a small improvement can supercharge your retention and revenue, but first you’ve got to know where to start.
In this blog, we’re going to help you navigate performing a churn analysis for your company and identify a churn issue before it gets out of hand.
Customer churn analysis is a way of understanding why and when customers are leaving your product. More specifically, it refers to the process of reviewing your company’s churn data to identify commonalities or patterns among customers that are churning.
For many SaaS startups, churn can be a silent killer. If you have a product that isn’t working smoothly yet, or you haven’t found the correct product-market fit, you’ll know right away with the lack of new customers or sign-ups. With churn, however, it could take months before you notice that something is wrong — if you’re not actively monitoring it. Here’s how a churn analysis lets you turn things around:
There are numerous reasons why customers may choose to leave your SaaS company or switch to a competitor. Here are some of the most common causes of churn:
Even from this short list, it’s apparent that each customer will have their own unique reason for leaving your product. A one-size-fits-all approach won’t work here.
A churn analysis allows you to dive deep into these causes and segment your audiences accordingly. You’ll understand which types of buyers are most likely to churn, and you can then target them with the right retention and loyalty strategies.
In other words, this analysis lets you go beyond your customer churn rate and avoid the trap of simply applying the same solution(s) to all your users. For example, if your company has churned customers due to a poor pricing strategy, you won’t be able to adopt the same strategy as a team that’s losing customers due to a lackluster or confusing onboarding process.
Recommended reading: A Guide to High-Touch B2B SaaS Onboarding
Based on the timeframes of when customers are churning, you can start to identify whether you have a sales problem, an onboarding problem, a customer success problem, or something else entirely.
Here are two quick examples:
Many SaaS teams are already great about collecting data, so using it to build a powerful churn analysis is a no-brainer. As you discover where changes need to be made and implement actions to curb your churn, you’ll have a set of metrics and KPIs to continuously reference. This will help your team stay on track and adjust your strategy as needed.
Although analyzing churn is the first step to reducing it, the truth is that churn is extremely hard to prevent altogether. According to Toward Data Science, the reason for this is simple:
“In order to prevent churn in a long term and reliable way, a service must actually improve either the benefit delivered by the service or reduce the cost incurred from using the service.”
There’s no silver bullet to reduce churn, and that’s why homing in on a solid churn analysis process — and sticking with it — is so important.
You’ve probably heard before that customer acquisition costs are always higher than the cost of retaining your existing customers.
So, it’s no surprise that another huge advantage of performing a churn analysis is that you’ll learn how much money you’re losing at any given point in the buyer’s journey — and concrete opportunities to get that money back. And as you lower your churn rate, your customer lifetime value (LTV) will increase, contributing to higher profits.
In addition, analyzing the hard numbers will allow you to better understand whether tools and services to prevent churn or optimize your customer journey (like Arrows for better onboarding) are worth the cost.
Less is more! In most cases, it isn’t necessary to analyze churn every week or even every month. Depending on the thoroughness of your analysis, it could be performed every six months to a year.
The reality is that a churn analysis done the right way takes a lot of work and a lot of data, especially for a small or growing team. (One way to cut down on the required time and effort would be to pull in data science professionals to assist you.)
If you’re in a position where you have localized teams, they could perform smaller churn analyses more frequently to understand their own effectiveness in their parts of the customer journey.
If your customer churn is happening more frequently (for example, if the average customer churns after three months), it might be necessary to perform a monthly churn analysis.
All that said, you should be regularly checking your churn rate to maintain a high-level view and notice any large spikes in either direction. This is especially true if you’re fundraising or working with venture capital firms.
Churn rate is a major variable in how investors perceive your business. In fact, venture capital firms consider customer churn one of the most critical SaaS metrics for raising capital, according to Jeron Paul, CEO and founder of Capshare.
Now comes the interesting part: Performing the churn analysis. These four steps will make the process manageable and organized, helping you draw out key insights about your customer churn without getting lost in the weeds.
The first and most important step in your churn analysis is mapping out your customer journey in as much detail as possible. You should be able to see all of the milestones and steps a customer should reach, the interactions they should have at each stage based on their segment, and the value they should receive at each of the customer lifecycle stages:
Check out our guide to creating a customer journey map to see how to navigate this process, step by step.
After mapping out your customer journey, you’ll want to gather as many datasets from the journey as you can for a year or as long as possible. This is where it can get a bit confusing if you’re not utilizing analytics tools.
We highly recommend you find an analytics tool that works for your company to ensure you have valid ways of measuring statistical significance, understanding what to measure from each part of the process and which teams influence which data points, segmenting customers, etc. Once your data is all in one place, you can modify the data to extract meaningful actionable insights as you see fit.
Next, identify when customers churn (the number of months, days, weeks, years after sign-up) and which stage is losing a significant number of customers. This includes determining which steps and/or actions they successfully took and which steps they didn’t.
You should draw out insights fairly quickly. For instance, maybe the customers who logged in at least eight times in two weeks were more likely to stick around than those who only interacted with your product three times in two weeks.
Once you’ve done this, then you can start to plan and deploy strategies to curb customer churn. Fighting churn is a joint effort among numerous team members — it isn’t something that can solely be done by AI, machine learning, or data science, though each can help.
Think about tapping into your product managers, software engineers, content creators, marketers, customer support representatives, and account managers. Each can play a vital role in reducing churn.
It’s important to understand the patterns among “like” or similar customer segments and cohorts. This allows you to make more accurate conclusions when customers in the same segment behaved differently.
For example, maybe you discover that the customers were onboarded in different ways. Maybe one customer received guidance and proper onboarding and the other attempted to entirely self-onboard without going through the typical program.
This process of customer segment is also referred to as creating churn profiles. A churn profile consists of common characteristics in your customer base, grouping customers by those common characteristics, patterns, and churn rates for each group.
One way you can organize your customer base is by the following:
Are customers churning during onboarding? Arrows can help.
After conducting a thorough customer churn analysis, you’ll have a clearer picture of where in your customer lifecycle your subscribers are dropping off. If you’re realizing that the issues are arising from your onboarding process, Arrows can help.
Arrows’ onboarding platform helps you set your customers up for success, allowing your team to easily create personalized onboarding plans by individual or cohort, optimize your onboarding process, and stop churn at the source.
Ready to see what Arrows can do for your team? Schedule a demo.
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