Abstract
The saturation of mobile phone markets has resulted in rising costs for operators to obtain new customers. These operators thus focus their energies on identifying users that will churn so they can be targeted for retention campaigns. Typical churn prediction algorithms identify churners based on service usage metrics, network performance indicators, and demographic information. Social and peer-influence to churn, however, is usually not considered. In this paper, we describe a new churn prediction algorithm that incorporates the influence churners spread to their social peers. Using data from a major service provider, we show that social influence improves churn prediction and is among the most important factors.
Original language | American English |
---|---|
State | Published - Nov 9 2012 |
Disciplines
- Bioinformatics
- Communication
- Communication Technology and New Media
- Computer Sciences
- Databases and Information Systems
- Life Sciences
- OS and Networks
- Physical Sciences and Mathematics
- Science and Technology Studies
- Social and Behavioral Sciences