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Customer Attrition Analytics : The Case of a Recruitment Service Provider


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1 Alliance University, Bengaluru, Karnataka, India
     

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Customer attrition is the phenomenon wherein a customer leaves a service provider. With the growing competition in the service sector, preventing customer attrition has become critical for sustainability, as it is well established that retaining existing customers is more profitable than acquiring new customers (Jacob, 1994). This gives customer attrition analytics the challenging task of predicting which customers are likely to leave, and of subsequently designing and implementing retention programmes for these customers. Customer analytics has made many strides in marketing, employer desirability, and branding, but has so far made limited strides in the recruitment industry space. The objective of the study is to identify the factors affecting a candidate’s decision to accept a job opportunity in an organisation, using predictors such as the industry verticals, the candidate’s skillsets, workplace location, gender, compensation offered, and the notice period of the candidate. The model developed is a logistic regression model, to determine whether a candidate selected will accept a job opportunity in an organisation or not. The analysis was performed based on a sample of 443 candidates who were provided job offers in the period 2013-2015 by a recruitment service provider.

Keywords

Customer Attrition Analytics, Factors Affecting Customer Attrition, Logistic Regression Models.
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  • Customer Attrition Analytics : The Case of a Recruitment Service Provider

Abstract Views: 33  |  PDF Views: 0

Authors

Mihir Dash
Alliance University, Bengaluru, Karnataka, India
Vishnu Raghavan
Alliance University, Bengaluru, Karnataka, India

Abstract


Customer attrition is the phenomenon wherein a customer leaves a service provider. With the growing competition in the service sector, preventing customer attrition has become critical for sustainability, as it is well established that retaining existing customers is more profitable than acquiring new customers (Jacob, 1994). This gives customer attrition analytics the challenging task of predicting which customers are likely to leave, and of subsequently designing and implementing retention programmes for these customers. Customer analytics has made many strides in marketing, employer desirability, and branding, but has so far made limited strides in the recruitment industry space. The objective of the study is to identify the factors affecting a candidate’s decision to accept a job opportunity in an organisation, using predictors such as the industry verticals, the candidate’s skillsets, workplace location, gender, compensation offered, and the notice period of the candidate. The model developed is a logistic regression model, to determine whether a candidate selected will accept a job opportunity in an organisation or not. The analysis was performed based on a sample of 443 candidates who were provided job offers in the period 2013-2015 by a recruitment service provider.

Keywords


Customer Attrition Analytics, Factors Affecting Customer Attrition, Logistic Regression Models.

References