Situations and Challenges: Improve return of investment for measures to make phone calls

You belong to the marketing department of a company that offers a flat rate service. Because the churn rate has a significant impact on business results, the marketing division implements measures to call customers to understand the reasons for withdrawal and to resolve complaints. Since most of the customers stay, the point is whether you can call the customers who are about to withdraw. In the past, you have narrowed down customers by age and gender, but in many cases you call customers who do not need a call policy, and narrowing down customers is an issue.

Using Predictive Analytics: Improved targeting with withdrawal prediction

• Prepare customer data (you will use sample datasets in the tutorial)
• Use Easy Predictive Analytics to predict the churn probability of each customer
• Create a list of customers with a high probability of churn to make calls

Expected Effect: Reducing the amount of customer churn

You can expect to reduce the amount of customer churn more than before because you can get more information about reasons for canceling and complaints by the calls.

Now let’s create a customer list based on the prediction with Easy Predictive Analytics.