Guide to Customer Retention Analytics- Part 2: Telecom Case Study
This post is a continuation of an earlier post on Customer Retention Analytics by our guest bloggers Sandhya Kuruganti and Hindol Basu, authors of a book on Business Analytics titled “Business Analytics: Applications to Consumer Marketing”. The first part of the post Guide to Customer Retention Analytics- Part 1 focused on understanding retention, attrition and the various retention strategies used by marketers. Part two will explain retention analytics, along with a Telecom Case Study that showcases the Proactive Approach to Retention Management using Churn Model.
Telecom Case Study: Proactive Approach to Retention Management using Churn Model
Data Preparation for Churn Model (Post Paid Segment)
Telecom Churn Model: The following table shows the potential predictors of Churn and sign of relationship. Logistic Regression is a popular statistical method that is used.
Implementation: Based on the churn mode l, a cut-off for the score can be decided. Subscribers exceeding the cut-off should be considered for contact. A suggested strategy could be:
Sandhya Kuruganti and Hindol Basu are authors of the book “Business Analytics: Applications to Consumer Marketing”, recently published by McGraw Hill and available on Flipkart and Amazon India/UK/Canada. Jigsaw students can avail of a discount of 20% with a coupon code at McGraw Hill website (valid until Nov 30, 2015). . The authors are seasoned analytics professionals with a collective industry experience of more than 30 years.
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