CUSTOMER CHURN ANALYSIS USING BINARY LOGISTIC REGRESSION MODEL

Mohammad Abiad; Sorin Ionescu

Article Details

CUSTOMER CHURN ANALYSIS USING BINARY LOGISTIC REGRESSION MODEL

Authors:

Mohammad Abiad | Sorin Ionescu

Publisher:

Beirut Arab University Press

Journal:

BAU Journal - Science and Technology Vol.1 Issue 2, pp.0-0

Document Type:

Article

Publication Date:

6/2020

Document Language:

English

Document ID (Org No.):

2001951481

pISSN:

2959-331X

Keywords:

Abstract:

 These days, the fundamental target of all organizations is to accomplish a reasonable gainfulness. Organizations are looking to decide the elements, which has direct impact on their benefit and attempt to investigate them so as to pick up favorable circumstances on their rivals. With this solid aggressive market, holding customers turns into the fundamental objective of telecom mobile service providers opposed to drawing in new customers, since the expense of holding a customer is viewed as low contrasted with the expense of pulling in another customer as referenced before by numerous researchers. Thus, Customer Churn Analytics is one of the significant elements that organizations should concentrate on to help their goal of accomplishing a reasonable benefit. In Telecommunication area, the business aims to serve customers, and analyzing customer churn will give the executives a thought regarding the probability of a customer to leave the organization. The primary goal of this paper is to highlight the main factors that affect customer churn and then analyze them by using the Binary Logistic Regression Model. A case study in Kuwait telecommunication section was taken as an application for such algorithm. A non-probability sampling technique is used (Snowball) to select a sample of 120 customer and analyze them by using the statistical software SPSS and MINITAB, results shows that the Customers’ Gender, Marital Status, Monthly Bill as well as the Service Quality have significant effects on Customer Churn.

Article Details

CUSTOMER CHURN ANALYSIS USING BINARY LOGISTIC REGRESSION MODEL

Authors:

Mohammad Abiad | Sorin Ionescu

Publisher:

Beirut Arab University Press

Journal:

BAU Journal - Science and Technology Vol.1 Issue 2, pp.0-0

Document Type:

Article

Publication Date:

6/2020

Document Language:

English

Document ID (Org No.):

2001951481

pISSN:

2959-331X

Telecommunication

Churn Rate

Binary Logistic Regression

Issues

Article Details

CUSTOMER CHURN ANALYSIS USING BINARY LOGISTIC REGRESSION MODEL

Authors: Mohammad Abiad | Sorin Ionescu

Publisher: Beirut Arab University Press

Journal: BAU Journal - Science and Technology Vol.1 Issue 2, pp.0-0

Document Type: Article

Publication Date: 6/2020

Document Language: English

Document ID (Org No.): 2001951481

pISSN: 2959-331X

Telecommunication

Churn Rate

Binary Logistic Regression

Issues

Authors:

Mohammad Abiad | Sorin Ionescu

Publisher:

Beirut Arab University Press

Journal:

BAU Journal - Science and Technology Vol.1 Issue 2, pp.0-0

Document Type:

Article

Publication Date:

6/2020

Document Language:

English

Document ID (Org No.):

2001951481

pISSN:

2959-331X