Churn prediction for mobile prepaid subscribers

Name: Churn prediction for mobile prepaid subscribers
Author: Can, Zehra, Albey, Erinç

İsim	Churn prediction for mobile prepaid subscribers
Yazar	Can, Zehra, Albey, Erinç
Basım Tarihi:	2017
Basım Yeri	- Institute for Systems and Technologies of Information, Control and Communicatio
Konu	RFM, Prepaid Subscriber, Telecommunication, Pareto/NBD, Logistic Regression, Mobile
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	978-989758255-4
Kayıt Numarası	adb5bda3-391a-40b5-b3d3-dc490db2fd80
Lokasyon	Industrial Engineering
Tarih	2017
Notlar	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Örnek Metin	In telecommunication, mobile operators prefer to acquire postpaid subscribers and increase their incoming revenue based on the usage of postpaid lines. However, subscribers tend to buy and use prepaid mobile lines because of the simplicity of the usage, and due to higher control over the cost of the line compared to postpaid lines. Moreover the prepaid lines have less paper work between the operator and subscriber. The mobile subscriber can end their contract, whenever they want, without making any contact with the operator. After reaching the end of the defined period, the subscriber will disappear, which is defined as “involuntary churn”. In this work, prepaid subscribers’ behavior are defined with their RFM data and some additional features, such as usage, call center and refill transactions. We model the churn behavior using Pareto/NBD model and with two benchmark models: a logistic regression model based on RFM data, and a logistic regression model based on the additional features. Pareto/NBD model is a crucial step in calculating customer lifetime value (CLV) and aliveness of the customers. If Pareto/NBD model proves to be a valid approach, then a mobile operator can define valuable prepaid subscribers using this and decide on the actions for these customers, such as suggesting customized offers.

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Özyeğin Üniversitesi

Kaynağa git

Churn prediction for mobile prepaid subscribers

Yazar Can, Zehra, Albey, Erinç

Basım Tarihi 2017

Basım Yeri - Institute for Systems and Technologies of Information, Control and Communicatio

Konu RFM, Prepaid Subscriber, Telecommunication, Pareto/NBD, Logistic Regression, Mobile

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 978-989758255-4

Kayıt Numarası adb5bda3-391a-40b5-b3d3-dc490db2fd80

Lokasyon Industrial Engineering

Tarih 2017

Notlar Due to copyright restrictions, the access to the full text of this article is only available via subscription.

Örnek Metin In telecommunication, mobile operators prefer to acquire postpaid subscribers and increase their incoming revenue based on the usage of postpaid lines. However, subscribers tend to buy and use prepaid mobile lines because of the simplicity of the usage, and due to higher control over the cost of the line compared to postpaid lines. Moreover the prepaid lines have less paper work between the operator and subscriber. The mobile subscriber can end their contract, whenever they want, without making any contact with the operator. After reaching the end of the defined period, the subscriber will disappear, which is defined as “involuntary churn”. In this work, prepaid subscribers’ behavior are defined with their RFM data and some additional features, such as usage, call center and refill transactions. We model the churn behavior using Pareto/NBD model and with two benchmark models: a logistic regression model based on RFM data, and a logistic regression model based on the additional features. Pareto/NBD model is a crucial step in calculating customer lifetime value (CLV) and aliveness of the customers. If Pareto/NBD model proves to be a valid approach, then a mobile operator can define valuable prepaid subscribers using this and decide on the actions for these customers, such as suggesting customized offers.