Customer Churn Rate

Customer Churn Rate (CCR) is the percentage of subscribers to a service who discontinue their subscription within a certain time period. In order for a company to expand its client base, the customer churn rate must be lower than its growth rate. Therefore, it is important to know what the CCR is as well as how to minimize it.

How To Measure Customer Churn Rate

Customer churn calculation is pretty straightforward. You have to take the number of customers you have lost during a specific time period and divide it by the number of customers you had in the beginning of the same time period.

Customer Churn Rate

For example, say you have 1000 customers at the beginning of the month, and 950 at the end of the month. This means that 50 customers were lost during that month. That means the CCR is 50 / 1000, or 0.05. That means that the customer churn rate is 5%. A good annual customer churn rate should stay between 5-7%. Anything higher may potentially be harmful for the company and should be worked at to be reduced.

For a more in depth explanation about how to measure CCR, take a look at this tutorial.

Why Measuring CCR is Important

It is important to keep a low CCR. If the churn rate is higher than the growth rate, that means the company is losing customers. When this happens, it is helpful to find out which customers are a churn risk. Knowing this allows actions to be taken that can minimize that risk. Measuring the churn rate of a company can help catch higher rates before they get too bad. For more information on identifying who is a churn risk, check out this tutorial here.

Customer churn rate is not to be confused with revenue churn rate. Revenue churn rate has to do with how much profit a company has lost during a given time rather than the number of customers. This is a better indicator to the health of the organization. While they are related, different insights can be drawn from both, meaning both should be tracked.

Steven McKim

About Steven McKim

Steven is a Senior at Virginia Tech studying Computer Science. Currently interning for Chartio, he helps with the Data School site as well as to keep them running smoothly and make them as user friendly and visually appealing as possible.

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