July 19, 2017 11:51 pm

What is Churn Analysis?

Customer churn analysis helps you identify customers who are likely to discontinue patronage, with a focus on higher value customers, and determine what actions typically preceding a lost customer or sale. When you improve customer retention, you substantially improve the bottom line.                   

A churn model predicts the likelihood of a client “churning”, (moving to a competitor or cancelling their business) by identifying predictable changes in consumer behaviour.

Benefits of Churn Analysis:

The output of a customer churn model can assist businesses in designing targeted retention campaigns, aimed at preventing high value, high risk clients from churning.

How it works?

Predictive models conducting churn analysis can be applied and benefit any sector where firms have a significant customer subscriber base.      

For instance, in the retail sector, this predictive analytics solution analyses factors such as:

  • the spending quantities,
  • time passed since last visit,
  • number of visits in a given time period,
  • customer clusters and so on to reveal which customers are shifting towards other stores to do their shopping.

Here is a simple and intuitive example of how churn analysis in telecoms is used in practice:

  • Users begin to reduce their mobile usage, analysts run the weekly customer churn analysis, and due to the reduction in usage, as well as a number of other predetermined factors, the model identifies these users as having a high propensity to churn.
  • The results are sent to the churn management system, which the company’s marketing team can review.
  • Based on this new information the marketing team can take action and target these customers in a personal retention advertising campaign. This campaign should entice those with high propensity to churn and assist the telecom company in retaining those clients by satisfying their needs and requirements.