Predicting Customer Churn in the Telecommunications Industry –– An Application of Survival Analysis Modeling Using SAS

by Junxiang Lu, D Ph
Techniques ()


Conventional statistical methods (e.g. logistics regression, decision tree, and etc.) are very successful in predicting customer churn. However, these methods could hardly predict when customers will churn, or how long the customers will stay with. The goal of this study is to apply survival analysis techniques to predict customer churn by using data from a telecommunications company. This study will help telecommunications companies understand customer churn risk and customer churn hazard in a timing manner by predicting which customer will churn and when they will churn. The findings from this study are helpful for telecommunications companies to optimize their customer retention and/or treatment resources in their churn reduction efforts.

Cite this document (BETA)

Readership Statistics

42 Readers on Mendeley
by Discipline
36% Computer and Information Science
17% Business Administration
10% Economics
by Academic Status
38% Student (Master)
17% Student (Bachelor)
12% Ph.D. Student
by Country
2% Germany
2% Hungary


Sign up today - FREE

Mendeley saves you time finding and organizing research. Learn more

  • All your research in one place
  • Add and import papers easily
  • Access it anywhere, anytime

Start using Mendeley in seconds!

Sign up & Download

Already have an account? Sign in