WHAT IS CHURN PREDICTION?

It costs five times more to attract a new customer than it does to retain an old one. In the world of ever-changing customers’ needs, retaining your old customers is crucial if you want to remain in business. Therefore, correctly predicting when your customers may want to leave is vital for sustainable business growth and success.

The rate at which a customer leaves a business is called churn rate. The dictionary defines “churn rate” as the annual percentage rate at which customers stop subscribing to a service or employees leave a job.

Reasons for High Churn Rate

There are many reasons why customers stop patronizing a business. The reasons could range from:

• Poor customer service: How customers feel about a business is greatly dependent on how the company treats them. customers are more likely to stop patronizing a business if they don’t feel loved, seen, heard and accepted. Customer service makes or mars a customer’s experiences.
• Better prices from Competitors: When a business’s competitor offers better prices and better customer experiences, a business is bound to lose customers.
• Economic changes: A change in a customer’s finance can be a major reason why he/she will stop buying certain goods and using certain services. It may be upward economic mobility or downward mobility.

Why Understanding Churn Rate is Important

Every business wants to stay relevant. Every business wants to make sales and make profits. If a business doesn’t know how much customers it’s losing, the business will be unable to properly plan and strategize on how to grow its business.

Understanding a customer’s lifetime value is imperative if a business is to take its churn rate seriously. A business which cannot properly contextualize its churn rate, and sees how much it affects the business if it does not know is most likely foolish.

Customers lifetime values are defining how much money a customer will spend in his/her lifetime on a business. When a customer is dissatisfied with the product or services a business offers, the customer would easily switch sides and patronise the business’s competitors.

It is important that a business knows and understands when a customer is about to leave, and do all that is necessary to retain the customer.

What is Churn prediction?

Churn prediction uses predictive analysis tool to determine when a customer will leave, and therefore device methods to retain a customer.

Predicting when a customer’s interaction with the business is reduced, or reducing, would help a business keeping old customers.

How to conduct Churn prediction analysis

Before using a predictive analytics tool, the churn prediction goal must first be understood. You can’t input data into the predictive tool if your goal isn’t specified from the start. The insights the tool will give you is dependent on what parameters you’re looking out for.

After you have defined what the goal is, the next step is inputting the relevant data that will be analysed.

There are two major types of churn data: Usage and contextual data.

Usage data is how much a customer used a business before they stopped, while contextual data refers to the contexts in which the customer used your business.

For example, a boutique will measure its usage data as the number of times a customer buys cloth from the store. And the context data will be the peak periods the said customer buys clothes.

The predictive analysis tool will then calculate the churn rate, providing the human analysts with enough information on how to stop the customer from leaving.

The solution to the customer leaving could be offering coupons, calling the customer, and many others.

Do you know your business’s churn rate?

Tell us in the comments below why you think some of your customers are leaving.