Open AccessA Comparative Study of Predicting Customer Churn and Lifetime
Author(s) -
O. Adesua,
P.A. Danquah,
O.B Longe
Publication year - 2020
Publication title -
advances in multidisciplinary and scientific research journal
Language(s) - English
Resource type - Journals
ISSN - 2488-8699
DOI - 10.22624/isteams/v26p1-ieee-ng-ts
Subject(s) - gsm , customer base , computer science , service (business) , telecommunications , key (lock) , artificial neural network , mobile telephony , focus (optics) , term (time) , business , customer service , marketing , artificial intelligence , computer security , mobile radio , physics , quantum mechanics , optics
The problem to be investigated in this research is that of predicting customers who are at risk of leaving the company, a term called churn prediction in telecommunication. The aim of this research is to predict customer churn and further focus on creating customer lifetime profiles. These profiles will allow the company to fit their customer base into n categories and make a long estimation on when a customer is potentially going to terminate their service with the company. The research then proceeds to provide a comparative analysis of neural networks and survival analysis in their capabilities of predicting customer churn and lifetime. . Key words: GSM networks, Base station, Mobile station, Signal strength, GSM service provider