Customer Churn

Quick definition: The number of customers an organization loses in a given timeframe.

Key takeaways:

• Churn rate is calculated by identifying the number of customers who have stopped engaging with an organization or using their services divided by the total number of customers, multiplied by 100, within a specific period of time.
• Simply looking at how many customers left may not offer as detailed a picture as looking at factors like the revenue loss that accompanied the customer churn.
• Companies can predict churn by examining customer actions to identify behaviors that indicate a high churn risk.
• With new technology, nearly every company can use churn data to their advantage.

The following questions were answered in an interview with Nate Smith, the Group Product Marketing Manager for Adobe Analytics.

What is customer churn?
Why is predicting churn important?
How do businesses reduce or prevent churn?
How can customer churn benefit a company?

The goal of any company is to attract customers and keep them for the long term. Unfortunately, companies can’t keep all the customers they onboard.

While drop-off is natural, businesses should remain vigilant in figuring out why customers are leaving and what they can do to be better. Identifying the reason for customer turnover starts with determining the customer churn rate.

What is customer churn?

Churn is a simple metric that refers to customer turnover. To put it simply, churn happens when a customer decides to stop using a company’s product or service. The more customer churning that takes place, the more customers are leaving your business for a competitor.

The goal of every business is to reduce churn and improve customer satisfaction. By improving customer retention, companies can build long-term profitability by keeping many of their customers happy.

The churn rate is the percentage of customers lost over a period of time and is typically attributed to a lack of compelling brand experiences that meet their needs, wants, or desires. Businesses need to know what their churn rate is to identify lost sales opportunities and refine their operations to stop the bleeding.

What is churn risk?

Churn risk refers to how likely a customer is to refrain from making repeat purchases from an organization. A company that is paying attention can identify warning signs, like a decreased number of logins, to determine the churn risk of a customer and take steps to retain them.

Red flags will be different for each business, so organizations need to consider business-specific metrics, interactions, and target markets to identify the potential churn risk of their customers.

How do you calculate churn?

To calculate churn, decide on a timeframe within which to examine performance. Divide the number of lost customers from one period to the next by the total number of customers in the former period, then multiply by 100.

The goal is to see how many customers remain at that lookback window. It’s essentially a division problem. For example, if a company has 100 subscribers on January 1, and 90 subscribers on February 1, the churn rate for that period is 10%.

Layering onto this equation, some companies consider seasonality or other specifics within a timeframe that could change the calculation.

Predicting customer churn

Predicting churn can also introduce new considerations, and often organizations will create models that can predict based on specific customer behaviors to see how those behaviors might affect churn.

For example, a business may look at the number of website logins as one of the factors for predicting churn. If the number of logins drops by a certain percentage, that could indicate a risk. A business could then take that information to identify customers who are at risk of churning and target them specifically.

Organizations usually have calculations to predict the number of customers or the number of subscriptions based on their churn rate or churn rate indicators, but one of the most important insights derived from a churn rate is calculating profit or revenue.

The Impact of Churn

Churn rate can significantly impact financial performance and forecasting.

Let’s say a company that sells enterprise software gets 100 new customers in a month, but by the following month, they’ve lost 10 customers, and now have 90. That’s a 90 percent retention rate, which might not seem bad. But if those 10 customers are responsible for 80 percent of revenue, the company has lost their most important customers.

The revenue impact from that churn rate is astronomical — while the customer churn rate is only 10 percent, the revenue churn rate is 80 percent. On the other hand, if a customer loses 10 customers that account for 20% of the revenue, the impact is not as harsh. Looking at multiple results of churn provides a more complete snapshot of the health of a business.

Why is predicting churn important?

Any organization can break down churn into components that they can use to make predictions. Running a predictive base churn rate on customers who are exhibiting certain behaviors, like irritation or indifference during the sales process, helps organizations be proactive to reduce churn.

Because churn is essentially the opposite of retention, reducing churn offers major benefits for companies. It costs money to acquire a paying customer. It's better to keep existing customers paying on an ongoing basis than to continually spend money trying to acquire new customers for a single transaction.

Why do customers churn?

While there are many reasons a customer might churn, at the root of it, customers leave because a business is no longer meeting their needs or wants. When a business breaks down its churn, it can start identifying what they’re not delivering to their customers. Because there are so many competitors serving the same consumer need, reducing churn involves being the best at satisfying every customer desire imaginable.

For instance, let’s say a company is paying a lot of money for their ads to show up on Google offering a luxurious Hawaii vacation. Eventually, the ads perform well and drive potential customers to the company’s landing page. If the customers click through to a landing page that has no mention of Hawaii and customers can't find the Hawaii offer, they're likely to churn and not come to the website.

Although the ad campaign may have driven traffic, it’s not expected to have acquired customers because the landing page didn’t align with the ad messaging.

Unsatisfaction Usually Leads to Churn

Every industry faces similar problems. For a business-to-business (B2B) company, the customer expectation could be post-sales service and support. If the customer doesn’t get that support, the next contract cycle could fall through.

At the end of the day, if the customers are unsatisfied or unhappy with their current experience with a brand, and think they can do better elsewhere, they will leave. Considering the different factors that influence churn can help keep customers happy.

How do businesses reduce or prevent churn?

There are a few things companies can think about. One is to be proactive. As soon as a company realizes they are losing customers and money, they should start doing analysis to break down the data by group, by revenue, by any other factor, and identify when and where people are leaving.

By analyzing the actions of the customers who leave, companies can identify some potential causal factors, and run tests on site content. For example, a company realizing they lost thousands of dollars from increased bounce rates can assess common exit pages from their website to determine where users are getting confused or frustrated. Split testing can be run on those pages to improve overall usability and to better align webpage content with user expectations.

As an organization acquires more data, it can determine the effectiveness of any changes made then continue to adjust. It's an ongoing process of refinement — investigate, refine, deploy, and then repeat the cycle until the problem is identified and addressed. Companies can also use artificial intelligence (AI) and machine-learning algorithms. These are game-changing technologies in the area of churn analysis and reducing customer churn.

What is a good churn rate?

A good churn rate for a company really depends on the industry, the product, the delivery, and a number of other factors. Each company will have to determine their own standard, but generally, a churn rate below 10 percent is considered a good number to aim for. Financial and retail companies usually have the highest industry churn rates.

How can customer churn benefit a company?

While a growing or high customer churn rate is an indication that a company is not meeting a customer’s needs or wants, it also can provide an opportunity for a company to re-evaluate their offerings and consider improvements. By looking at the churn rate with both long- and short-term lenses, a company can determine whether the cause of increased churn is a short-term problem, like an issue with the website, or a long-term problem, like a disruption in the industry. By paying attention to churn rates, companies can continually evaluate the experiences they provide to customers and keep evolving to meet their audience’s expectations.

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