A Survey and Implementation of Machine Learning Algorithms for Customer Churn Prediction

Main Article Content

Snehal Rathi, Atharva Puranik, Vaishnavi Pophale, Prajwal Kutwal, Vibhav Kulkarni, Shaantanu Pratham, Vikas Maral

Abstract

Estimating customer traffic is an important task for businesses because it helps them identify customers who are most likely to leave and take preventative measures to retain them by improving customer satisfaction and further increasing their own revenue. In this article, we focus on developing a machine-learning model for predicting customer churn using historical customer data We performed engineering operations on the data, addressed the missing digits, coded the categorical variables, and preprocessed the data before evaluating it using a variety of performance indicators, including accuracy, precision, recall, f1 score, and ROC AUC_Score. Our feature significance analysis revealed that monthly fees, customer tenure, contract type, and payment method are the factors that have the most impact on forecasting customer churn. Finally, we conclude the best-performing model, the Soft Voting Classifier, implemented on the four best-performing classifiers with a good accuracy of 0.78 and a relatively better ROC AUC_Score of 0.82.

Article Details

How to Cite
Snehal Rathi, et al. (2023). A Survey and Implementation of Machine Learning Algorithms for Customer Churn Prediction. International Journal on Recent and Innovation Trends in Computing and Communication, 11(10), 1062–1069. https://doi.org/10.17762/ijritcc.v11i10.8625
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Articles
Author Biography

Snehal Rathi, Atharva Puranik, Vaishnavi Pophale, Prajwal Kutwal, Vibhav Kulkarni, Shaantanu Pratham, Vikas Maral

Dr. Snehal Rathi1, Atharva Puranik2, Vaishnavi Pophale3, Prajwal Kutwal4 , Vibhav Kulkarni5, Shaantanu Pratham6, Prof. Vikas Maral7

1Department of Computer Engineering

Vishwakarma Institute of Information Technology, Pune, India

snehal.rathi@viit.ac.in

2Department of Computer Engineering

Vishwakarma Institute of Information Technology, Pune, India

atharva.22010869@viit.ac.in

3Department of Computer Engineering

Vishwakarma Institute of Information Technology, Pune, India

vaishnavi.22010473@viit.ac.in

4Department of Computer Engineering

Vishwakarma Institute of Information Technology, Pune, India

prajwal.22010845@viit.ac.in

5Department of Computer Engineering

Vishwakarma Institute of Information Technology, Pune, India

vibhav.22010011@viit.ac.in

6Department of Computer Engineering

Vishwakarma Institute of Information Technology, Pune, India

shaantanu.22010051@viit.ac.in

7Department of Computer Engineering

Vishwakarma Institute of Information Technology, Pune, India

vikas.maral@viit.ac.in