## Churn rate definition

Churn rate is a broad term referring to the action of people leaving a specific group in a given amount of time. So it can be applied to employees leaving a company or to customers that end their subscriptions to service for example.

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In this article, weâ€™ll address the customer churn rate in particular as the measure of the number of customers that stop their interaction with a company. The churning customers might have been involved in a subscription type of service (think SaaS, cable and phone companies) or they just repeat buyers that donâ€™t have a fixed frequency (think e-commerce stores).

## SaaS churn rate formula & calculation

Churn rate is one of the most important KPIs for SaaS (software as a service) companies since it can be used to predict the company growth. The time span itâ€™s usually calculated for is either a month or a year. And the churn represents the percentage of customers that have stopped their subscription from the total amount of customers. Thus it can easily be calculated like this:

Churn rate = (number of lost customers / total amount of customers) * 100

For example, if we have a company that loses 10 customers form a 1500 customer base, the churn rate would be (10/1500)*100 =  0.66%

## E-commerce churn rate formula & calculation

Calculating the churn rate for e-commerce stores is equally important, however, unless youâ€™re running a subscription-based site, itâ€™s not that easy to make this calculation. So because in the case of regular e-commerce stores there is no definite action which a customer can make in order to be clear that they are churned, we need to implement an arbitrary cutoff date in order to be able to make this calculation.

This cutoff date can be set by analyzing the trends of previous transactions for example. In the case of repeat buyers, for example, thereâ€™s an average time span between purchases. Depending on the industry it maybe 1 week, several weeks, several months or even more than one year. Using this data as a cutoff time, for example, enables e-commerce owners to calculate churn rates using the same formula as the one stated above.

## Customer churn analysis

Tracking the churn rate is the first important step but interpreting and analyzing the data is what makes this effort worthwhile for business owners. By tracking the number of churning customers together with the amount of income generated by them, a clear direction of the business can be seen.

In the analyzing stage, one of the most important tasks is discovering patterns in order to quickly address major problems before they have a big negative impact on the business. This is why it can be very useful to track the churn rate evolution for a number of important customer segments. Some of them might be:

• Demographics (age, gender, location)
• Cohorts (customers from a specific month or year)
• Customer industry
• Customer size according to the amount of revenue generated

## How to reduce the churn rate (aka churn rate optimization)

After tracking and seeing the current state of the churn rate overall or for specific customer groups, a business owner might decide to invest resources for decreasing it. Depending on where the main problem lies, there are different strategies and techniques that can help reduce the churn, such as:

• Having a responsive client support team
• Implementing personalized messages that get sent at key moments in time (for example just before customers are going to churn)
• Activating promotions and deals in order to make the renewal decision much easier
• Improving the website usability to that visitors can easily find their way
• Running customer satisfaction surveys in order to discover the users unmet needs
• Investing in branding and brand loyalty
• Creating an RFM model
• Implementing advanced ad campaigns (such as remarketing according to the user behavior)
• Under promising and over-delivering
• Tracking your company’s NPS score
• Implementing up-selling, down-selling and cross-selling

## Customer churn rate by industry

Churn rate varies a lot from industry to industry and according to the size of the company. Companies with a smaller client base tend to have higher churn rates, while those with large client bases tend to have smaller churn rates, but this is not always the case. Itâ€™s very difficult to make generalizations especially because churn rates are not usually made public.

For SaaS companies, for example, an acceptable churn rate is around 5%. But depending on the vertical theyâ€™re in it can vary with about +/- 2%. Other known average churn rate values include:

• European telecom companies: 20-38%
• American credit card companies: 20%
• Retail banks: 20-25%

But even within a single industry churn rate can vary greatly, so ideally, the target churn rate should be calculated by each company according to their own KPIs such asÂ customer lifetime value,Â average order value,Â monthly recurring revenue, etc.Â