Metrics Monday 01: Churn Rate
A new short-and-sweet weekly(ish) post, because I like metrics and I like alliteration.
I was first introduced to customer churn while freelancing for a marketing agency. Their client, a national chain of fitness clubs, needed to know the drivers of their churn rate, which had increased over the second half of the year. Though there are some nuances and variations between companies and industries, the concept is fairly easy to grasp. Salesforce provides the most succinct and helpful definition I’ve found:
Churn rate, sometimes known as attrition rate, is the rate at which customers stop doing business with a company over a given period of time. Churn may also apply to the number of subscribers who cancel or don’t renew a subscription. The higher your churn rate, the more customers stop buying from your business. The lower your churn rate, the more customers you retain. Typically, the lower your churn rate, the better.
Again, there are variations, but the calculation for churn rate is something like this:
customers lost during a time period / total number of customers at the beginning of the same time period
My imaginary (FOR NOW!) food subscription service, Nicole’s Noodles, sends our customers 4 ounces each of three different types of noodles every month. In June, our box contained hearty Japanese soba (buckwheat) noodles, light and delicate Italian fedelini, and quick and easy glass noodles.
We had 2,812 customers on June 1 and lost 271 between June 1 and June 30 (for simplicity’s sake, let’s say I didn’t attract any new subscribers during that same period), my churn rate for June would be 9.6%. Ouch. Maybe the buckwheat was too heavy for the summer.
With inflation and economic uncertainty on the rise, I expect businesses providing non-essential goods and services will see increased customer churn if they haven’t already. That Sips By box might just fall victim to the budgetary axe, but perhaps Celestial Seasonings or Bigelow will see higher sales from thrifty tea drinkers.
Since customer churn is an actionable metric, analysts should be ready for stakeholders to request insights in this area. Take the initiative to lay the groundwork for calculating accurate, meaningful churn rates. Find your company’s data governance committee-approved definition of churn rate in your data dictionary. (I know, I know. You probably don’t have one of those, but perhaps you should kick off an initiative to define your company’s key metrics.) In the absence of a formal definition, find the subject matter expert(s) on the topic. While you’re at it, find out how your company defines a customer. (Don’t laugh. Go ask a few different people in your organization to define a customer.)
Once you’ve defined “churn rate” and “customer”, don’t just calculate the metric. Dig into the data — what patterns do you observe? I’ll provide two straightforward examples, but consider as many factors as you can in the time available.
Despite a number of lost newer customers, does your company have a large number of loyal customers? Perhaps one of your recommendations could be to focus on customer retention rates (which I’ll cover more in-depth next Monday) by investing in that segment of customers.
Have organizational events impacted churn? Maybe the customer experience team overhauled their processes and started using a new service management platform last month, and as the team was adjusting to the new workflow and new software, their turnaround times increased and customer satisfaction rates decreased as a result.
I said short and sweet, so I’ll end there. Next week we’ll look at customer retention rates. If there are any metrics you’d like me to cover, hit me up in the comments or on Twitter.