Churn analysis: a practical guide


What is churn?


Why churn analysis matters


What to consider when doing churn analysis


Investigate customer churn with two types of data


How to prevent churn


Automate feedback analysis to prevent churn


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A leaky bucket in business lingo means you’re losing customers. Every company has some customer churn. A significant amount of churn can be a sign of problems with the product or the customer experience—or it could be due to changing market trends. By conducting customer churn analysis regularly, you can identify issues and course-correct. 


What is churn?

A customer has churned when they’ve stopped using your product or service. It’s usually expressed as a rate of change over a specific period of time:

Number of lost customers / number of total customers. For example: 7 lost customers / 100 total customers = 7%

That percentage can be tracked monthly, quarterly or yearly. 

An increase in churn tells you that customers are getting less value from your product than before. Perhaps it no longer meets their needs as well as it once did. Or the user experience is worse as new features have been added. Whatever the cause, it’s important to find out what’s going on so you can improve the customer experience and plug the leaky bucket.


Why churn analysis matters

Some churn is expected. Some churn is even healthy: if your product solves a specific problem for a certain type of user, it won’t be a good fit for everyone. As a result you might end up with a few customers whose problems aren’t aligned well enough with your offerings and they’ll eventually leave.

Likewise, you’re bound to see some attrition for reasons out of your control. Customers may not want to stop using your product but if their conditions change, they could be left with no choice.

Why not aim for zero churn? A business that sees no churn at all is likely not expanding into new markets aggressively enough.

If your churn rate is both low and pretty consistent over time, it’s a healthy sign.

What is a low churn rate? It depends on the category. Various studies suggest churn rates below 10% are ideal particularly in the tech industry. Other analyses take into account business models. For example, B2B companies might see higher churn rates among their small and medium sized business customers than their enterprise ones because enterprise businesses are usually better positioned to weather ups and downs.

It's best to establish your own baselines and factor in what you know about your customers.


What to consider when doing churn analysis

Variation in the churn rate is the metric to keep an eye on. It’s important to know if you’re losing customers at a higher rate than usual so you can look into the cause and fix it. There are a few things to consider when doing churn analysis.

Analyze churn by segment. Once you’ve identified higher-than-usual churn, it helps to understand who’s churning. Whether you segment customers by geography, usage, purchase frequency, product type, spend/tier, industry, size, device type (particularly for ecommerce or subscription services), and more. Segmented churn analysis helps you prioritize.

If your biggest spenders are driving your increased churn rate, you’ll want to prioritize understanding why and addressing it as soon as possible. It may turn out that, for instance, a strategy meant to increase engagement among occasional spenders was a big turn off for your biggest spenders.

Understand what churn includes. The churn rate, or net lost customers, is made up of both the number of customers lost and the corresponding revenue loss. A healthy churn rate means you’ve acquired more new customers than lost existing ones. It also means logging more upsells than downgrades.

Know your revenue and lifetime value per customer. Revenue lost as a result of churn is measured by the contract value (ACV) or revenue per lost customer. Customer lifetime value (LTV) in total and by segment will give you a sense of the economic impact of each lost customer.

Take into account customer acquisition cost. Studies indicate that acquiring new customers is more expensive than retaining existing ones. It’s worth knowing your specific customer acquisition cost (CAC). Say your customer lifetime value is $5,000 and customer acquisition cost is $1,000. Your LTV to CAC ratio is 5:1. Since it will cost you, on average, $1,000 to replace a customer, your average customer lifetime value will go down if your churn rate goes up: it takes more to recoup losses since customer acquisition cost will likely remain constant.


Investigate customer churn with two types of data

Metrics to watch for warning signs of potential customer churn include:

  • Usage/engagement rates
  • NPS scores
  • App store ratings
  • Number of support tickets

Tracking these metrics over time just as you would track churn over time helps you prioritize. 

While numbers-based measures tell you what is happening with your customers, they don’t tell you why. To understand why customers churned or may soon churn, look to these sources of customer feedback:

  • Exit surveys or exit interviews
  • NPS open ended feedback
  • Support ticket verbatims
  • App store reviews or online reviews

You’ll want to analyze customer feedback to figure out if there are changes in customer expectations or needs, product performance, or the customer experience. Exit surveys can provide direct feedback on why a customer stopped using you. Exit interviews, though not as scalable, give you a chance to dig deeper into a customer’s answers. 

Analyzing other feedback such as open ended answers from NPS surveys, support tickets, and app store reviews/online reviews will give you insights on how to improve your product or customer experience much faster than not analyzing feedback at all.


How to prevent churn

Analyzing and acting on insights to prevent future churn includes taking a close look at every part of the customer experience. Qualitative analysis of customer feedback, for example, will tell you exactly where to focus. Here are four things you can do to prevent customer churn.

Formalize feedback loops as part of product development. You already know that quantitative analysis of customer behaviors combined with qualitative analysis of customer feedback will tell you what customers do and why, including churn. Formalizing feedback loops as part of your product strategy will give it more legs than doing it ad hoc.

It’s easier to build rigor around feedback collection, analysis, and insights extraction if a cross-functional team is involved, including product management, customer support, customer operations, and user research. At top performing companies, marketing and sales teams also participate in this process.

Scrutinize the end-to-end customer experience. Customers who have a great experience from the moment they land on your website to the moment they get first value from your product are more likely to stick around. That includes a great customer experience for:

  • Product information that clearly explains your value proposition
  • The trial sign up process
  • Onboarding
  • Customer support during trial
  • The user interface
  • Product navigation
  • The conversion or upgrade process 
  • Ongoing customer support
  • Learning about and trying new features

Shorten time to value. The less friction a customer faces when signing up for and starting to use your product, the sooner they’ll reach the first moment of value with your product. Customers getting benefit from your product early are less likely to give up and look elsewhere to meet their needs.

Segment and personalize the customer experience. Instead of building a one-size-fits-all experience for customers, aim for personalizing your communication, support, and product delivery by segment. You’ll be able to prioritize your highest value customers while also creating more turnkey offerings that serve your secondary segments well.



Automate feedback analysis to prevent churn

Getting to the bottom of why customers churn is possible when you analyze their feedback. Viable automates qualitative feedback analysis so you can understand what’s driving churn in a systematic way and stop it faster.


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Viable Team

Staff

Last Updated: 09/08/21

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