Customer Churn Analysis
Churn is when customers stop using a product or service. It also refers to when customers close an account with a service provider or stop shopping at a store, when clients stop using a SaaS product or cancel a subscription. Businesses use customer churn analysis to understand why people leave.
Customer churn analysis — an overview
No company wants to lose customers. But it is a fact of life for any type of business. That’s why companies put so many resources into preventing and reducing churn. Here is a breakdown of different kinds of customer churn:
- Financial institutions (banks, electronic trading platforms): Customers close their accounts
- Media companies (video streaming sites, magazines, newspapers): Customers cancel their subscriptions
- Telecommunications services and SaaS platforms(cell and internet connection, subscription software products): Subscribers don’t renew their contract or service agreement, or simply sign up with a different provider
- Retail stores and wholesale warehouses: Customer stop shopping at a store or go to a different supplier
What are the benefits of churn analysis?
If losing customers is one of the downsides to running a business then churn analytics is one of the upsides. Companies use a customer churn analysis tool to understand why customers leave so they can take actions to reduce churn. Why not just replace ex-users with new users? Because acquiring new customers can cost five times more than retaining existing users.
There are many other benefits of customer churn analytics:
- Improve customer service
- Improve UX and UI
- Reduce revenue loss
- Lower new customer acquisition costs
- Reduce sales and marketing costs
Churn analytics real life examples:
- Messaging app: Viber improved its app interface and reduced churn
- Media and entertainment: A Fortune 100 media company cut churn and increased viewer consumption
- B2B SaaS: Comarch is a business IT software company that drove loyalty and reduced churn.
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How does customer churn analysis work?
Customer churn analysis software tracks users’ journeys and identifies steps taken prior to closing an account, canceling a subscription, or even not returning to a store to purchase products. This information can reveal what went wrong for a customers — or even a cohort of customers. Analytics can reveal that a user is not getting the full value of a platform because they’re logging in a few times per month or that a website has an onboarding funnel with extraneous steps. There are a lot of reasons why someone would cancel an account with a service but the unique thing about running a customer churn analysis review is that it illustrates customers’ exact experiences, which goes a long way in helping a company make improvements and A/B test retention strategies.
How to analyze churn
A great way to understand how churn analysis work is by looking at how things worked in the past (and how some companies still do it).
Before customer churn analytics emerged as a cutting edge process for understanding why people leave, companies would rely on customer service agents or feedback forms. But it has been estimated that about 97 percent of users churn without leaving feedback.
As an example of the benefits of a customer churn analytics, consider the following scenarios:
Customer A: A SaaS platform subscriber goes to her profile page and cancels her account. She bypasses the feedback form. The company has no information about why Customer A left.
Customer B: Another SaaS platform subscriber calls customer service and says he wants to end his service. The representative asks Customer B if he wants to give a reason for not renewing. The customer declines and ends the call.
In both of these examples, neither the feedback form nor customer service was able to identify why the customers closed their accounts.
With churn analytics, companies are in a much more advantageous position. The customer success team sees a report that details a user’s experience (also cohorts who are at risk of closing their accounts) and reveals the last steps taken by the customer before leaving. For Customers A and B above, their last moment with the product was not the reason they unsubscribed from the SaaS platform. But rather, user journey analytics reveals that in the steps prior to Customer A going to her account page and Customer B calling customer service, A spent a much longer time than most other users in the site’s onboarding funnel and B was only using the software two or three times per month. This is a lot of great information. Now the company has something to work with.
The customer experience team can evaluate the onboarding funnel and remove areas of friction that made Customer A so frustrated that she closed her account. As for Customer B, perhaps he would have used the platform more if he had been provided a few tips for getting more use out of the software.
Of course, this is just a sample of the power of churn analytics. Using a tool like this doesn’t prevent customers from taking their business elsewhere, but it does empower companies to improve the issues that cause customers to leave. And in turn, companies pay less to retain existing users than they would pay to replace those users with new customers.
“The bottom line,” according to a Bain & Company, a management consultancy in Boston, ” is that increasing customer retention rates by 5 percent increases profits by 25 to 95 percent.” So the goal should be fixing the issues that cause churn.
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