In the world of ecommerce, merchants must face multiple challenges during their day-to-day operations. Among those many challenges, customer churn is probably the most distressing.
Most ecommerce merchants spend hundreds of thousands of dollars each year to acquire new customers, only to lose existing ones over the same period. This activity cycle can be somewhat daunting, even for the most experienced online merchants.
While the reasons for customer loss are both readily visible and sometimes unknown, what’s important is how to track and calculate customer churn rate.
Without knowing or monitoring customer churn rate, you’ll be unable to accurately analyze your customer growth/loss trend. Also, you’ll be unable to fully understand or calculate key metrics such as customer lifetime value.
Therefore, calculating customer churn rate is extremely important to make critical business decisions. Let’s quickly look at what it is and how to calculate it.
What is Customer Churn Rate?
It is an essential metric to assess the health and stability of your ecommerce business. A high churn rate means you’re losing customers more often, which will negatively impact your bottom line.
For example, as seen in the illustration above, if you’ve acquired 10 customers this month and 3 customers leave your store before the end of the month, then your customer churn rate is 30% for the month. And that may not be a good number!
While it may look easy to calculate and find these insights, calculating and analyzing customer churn can get a little complicated when the volume of customers increases.
The complexity required to find the results, when bigger numbers are involved, can lead to wasted time and missed opportunities. Infact, you may end up spending more time trying to qualify churn rate, instead of using the metric to grow the revenue of your business.
That’s why you need an easy way to calculate customer churn effectively.
So, let’s look at the three formulas that can help you make this calculation easier. (Although you can use Bloom Analytics to make the process super fast)
Customer Churn Rate Formulas
Let’s start with the basic formula
Simple Customer Churn Rate Formula
The easiest way to calculate churn is with the help of retention. If you know your retention rate then you can use the below formula to find the churn rate.
Churn Rate = 1 – Retention Rate
So if your retention is 80%, then your churn rate is:
1 – 0.8 = 0.2 or 20%
Pros & Cons of this formula
The primary advantage of this formula is that it’s very easy to use and find churn. You just need to know the retention rate and voila, you will know the churn.
However, this formula’s strength is also its weakness.
It is heavily dependent on the retention rate.
If you’re already tracking your customer retention rate then all props to you. But if you’re not then it’s going to be a monumental task to find the retention rate.
Using analytics applications will definitely make this process easier because most applications, like Bloom, integrate with your online store and automatically gather customer and sales data. So, your customer retention is recorded and therefore, churn rate is easier to find.
However, if you’re relying on spreadsheets, then the next formula could help you better.
Better Customer Churn Rate Formula
A better version of the customer churn rate formula is:
Churn Rate = ((Beginning Customers – Ending Customers) / Beginning Customers) X 100
You can also calculate Average churn over a period of time using the below formula:
Average Churn = ((Ending Period / Beginning Period) ^ (1/ Periods)) – 1
We’ll look at a detailed calculation using this formula in just a bit.
The best part of this formula is that it considers the total number of existing customers and the total number of lost customers within a given period of time. You can also use it to calculate average churn rate for your customer base over the given period of time.
Now let’s look at how to calculate churn rate.
How To Calculate Customer Churn Rate
We will look at how to use both the formulas in a spreadsheet and you can also download the template.
Using The Simple Formula
For this calculation, we have considered a retention rate of 80% and the churn rate is 1-80% which results in 20%.
Using The Better Formula
As you can see,
Churn Rate = ((6000 – 4000) / 6000) X 100 = 33.33%
Average Churn = ((4000/6000) ^ (⅕)) – 1 = 7.79%
Based on these figures, you can now make critical decisions on how to reduce your customer churn rate.
Here’s The Free Customer Churn Rate Template.
How to Reduce Customer Churn Rate
Now that’s a fantastic question. We’ve covered an extensive article around the different ways to reduce ecommerce churn rate. You should check it out.
But to give you a heads up, here are some ways that can help you reduce churn.
- Ensure your product resolves customer’s needs and problems
- Improve customer experience and satisfaction
- Ensure timely delivery of products every time
- Reward loyal customers
- Communicate with your customers regularly
- Act upon the feedback you get from customers
These are some ways that you can improve your customer relationship and reduce customer churn.
However, do remember that some reasons are totally out of your control.
For example, if your ecommerce store is a localized business and your customer has moved to a new location, then it’s not your fault the customer stops buying from you.
You also need to factor in voluntary and involuntary churn. Voluntary churn refers to a customer exiting your business with a well-defined reason, such as they don’t like your products anymore or they’ve found a competitor offering better products at better pricing.
On the flipside, involuntary churn refers to losing customers due to payment failures, transaction failures, etc., which are generally not direct customer decisions. The example mentioned above about customers moving to a new location can also be considered involuntary.
Likewise, there are many reasons why customers stop doing business with you. Your job as an ecommerce store owner is to ensure you give your customers the best product and service. The rest is left to the customer’s choice.
How to Analyze Customer Churn Rate Using Customer Cohorts?
You may have noticed that we used the words “cohort of customers” quite a bit in this article.
A cohort of customers refers to a group of customers with a specific characteristic.
For example, customers acquired from your discount coupon campaign are one cohort of customers, whereas customers obtained from your loyalty program are another set of customers.
You’d want to analyze customer churn rate and other metrics for both of these cohorts.
Because one cohort of customers may leave your business for reasons different from the other cohort of customers. Though you may mix both cohorts to analyze churn, it is generally advised to do it separately.
You may also analyze churn for both these cohorts against each other to find better insights.
Here’s a typical example of analyzing churn rate using cohorts:
As you can see, customer cohorts are generally grouped by time periods such as weeks, months, and years. However, you may segment customers based on unique characteristics and analyze their churn rate.
Using advanced ecommerce analytics applications such as Bloom can definitely help you in this cause.
But there is still one question that needs to be answered.
Why is it important to analyze churn using cohorts? Aren’t there better methods?
Well, churn rates fluctuate very rapidly in an ecommerce business, and it’s important to find these fluctuations accurately to make the right business decisions at the right time.
When you group your customers in a cohort, you can easily analyze these trends over a period of time and make decisions quickly.
If you use traditional methods or spreadsheets, you may find it overwhelming to track customer churn rate for each customer.
That’s why cohort analysis is the best way to analyze churn rate.
Use Bloom Analytics to Easily Analyze Customer Churn Rate
As an ecommerce entrepreneur, you do a million things to keep your store thriving and meet business goals. However, to make important decisions that lead to success, you need insights on various critical metrics.
Quite often, maintaining data for these metrics such as churn rate, and then deriving insights from them can be challenging.
But, the fact is that it shouldn’t be that difficult. It should be as easy as plug and play.
That’s exactly how we’ve built Bloom analytics for ecommerce owners. Bloom integrates with your Shopify store in a few simple steps and then provides you with insights that you’d never have imagined.
And these are actionable insights at a granular level.
From cohort analysis to product analytics, Bloom can make your everyday decision making super easy by gathering data from every nook and cranny of your business, and visualizing it in a simple format.
You can try Bloom today to make a difference to your ecommerce business.
Sign up for our free trial!
Customer Churn Rate – Frequently Asked Questions (FAQs)
Q. Why is customer churn important?
A. Customer churn reveals the number of customers leaving your brand. So if you’re tracking it, then you will know how your revenue is getting affected every time customers leave your brand.
A higher churn rate also reflects a lower retention rate. Churn will have a direct impact on the customer base you acquired and their lifetime value. By gaining this insight, you can make necessary decisions to improve your business, such as improving your customer experience when they purchase your products.
Q. Is calculating customer churn rate complex?
A. Calculating customer churn depends on the volume of data that you’re handling. From a technical standpoint, the customer churn rate formula is quite simple and can be used by any ecommerce store owner easily.
However, calculating customer churn when you have a large group of customers and various cohorts can get complex.
You can use ecommerce analytics applications such as bloom to uncomplicate the process and spend more time in growing your business.
Q. How is customer churn related to other ecommerce metrics?
A. Customer churn rate is used to calculate various other metrics in the ecommerce world. Here are some of them that need churn rate:
- Retention rate – One of the primary metrics that churn rate is used for is to calculate retention rate. In fact, both these metrics are like yin and yang. If you have one metric you calculate the other. Because retention rate is equals 1 – churn rate and Churn rate is equals 1 – retention.
- Weighted Average Gross Profit – You can use retention rate or churn rate to calculate weighted average gross profit. The formula for that is gross profit * retention rate.
- Customer lifetime value – The most important metric that churn rate is used for is to calculate lifetime value. Here’s a CLV template that uses churn rate.
Q. Which is the best way to keep track of customer churn for Shopify stores?
A. If you’re a Shopify store that has just launched then you may start tracking customer churn using a spreadsheet. However, when you start growing then you’d need a robust analytics application that can get the work done.
A primary reason for that is the lackluster nature of in-built Shopify reports. They’re very limited to a few marketing reports. Even if you subscribe to Advanced Shopify or Shopify Plus plans, you’ll be unable to analyze critical business metrics.
So, as you’re scaling your Shopify store or even if you’re an established Shopify store, the best way to track customer churn is with the help of an analytics application, that’s available in Shopify app store.
What are the best Shopify analytics applications to track and analyze customer churn?
A. There are quite a few analytics applications that can help you with critical ecommerce metrics including churn rate. Here are a few reputed.
Bloom Analytics – Bloom is built specifically for shopify stores and merchants. Bloom is also built by the same team behind Data Export Reports and Report Pundit, two best shopify apps for reporting analytics. So, you can use bloom to track essential metrics.
Lifetimely – Lifetimely is an analytics platform which is pretty good with predicting customer lifetime values. So if finding customer lifetime value is your only requirement then you may use this application.
Peel Analytics – Peel analytics has good automated mechanisms to provide insights. So if you need to automate any insights specifically on a timely basis then you may use Peel.
Polar Analytics – Polar analytics is a multi-channel analytics platform for your ecommerce business.