Work

Customer Churn Prediction Using Machine Learning

Year: 2025

Type: article

Abstract: Customer churn, where users stop using a service, is a major challenge, especially in telecom. Predicting churnhelps businesses retain customers more cost-effectively than acquiring new ones. This study uses machine learningmodels—SVM, Random Forest, and Decision Trees—to analyze customer data. Random Forest performs best inaccuracy, precision, recall, and F1-score. Integrating these models into CRM systems helps identify at-riskcustomers early. Targeted retention strategies reduce churn and improve customer loyalty. Machine learningenhances consumer behavior prediction. The study provides key insights into churn dynamics.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15100335

Authors: Fouzia Sulthana, K.Ravi Teja, K.Adithya, K.Yashwanth, K.Sai Krishna

Language: English

Topic: Customer churn and segmentation

Subfield: Marketing

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W6949281377

FWCI:

Cites:

Cited by:

Related to: