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Telco churn prediction with big data

conference contribution
posted on 2024-10-31, 18:30 authored by Yiqing Huang, Fangzhou Zhu, Mingxuan Yuan, Ke DengKe Deng, Yanhua Li, Bing Ni, Wenyuan Dai, Qiang Yang, Jia Zeng
We show that telco big data can make churn prediction much more easier from the 3V's perspectives: Volume, Variety, Velocity. Experimental results confirm that the prediction performance has been significantly improved by using a large volume of training data, a large variety of features from both business support systems (BSS) and operations support systems (OSS), and a high velocity of processing new coming data. We have deployed this churn prediction system in one of the biggest mobile operators in China. From millions of active customers, this system can provide a list of prepaid customers who are most likely to churn in the next month, having 0.96 precision for the top 50000 predicted churners in the list. Automatic matching retention campaigns with the targeted potential churners significantly boost their recharge rates, leading to a big business value.

History

Start page

607

End page

618

Total pages

12

Outlet

Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data

Name of conference

The 2015 ACM SIGMOD International Conference on Management of Data

Publisher

Association for Computing Machinery

Place published

United States

Start date

2015-05-31

End date

2015-06-04

Language

English

Copyright

© 2015 ACM

Former Identifier

2006053912

Esploro creation date

2020-06-22

Fedora creation date

2015-07-02

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