Year: 2025
Type: article
Abstract: In this work, a comprehensive customer churn analysis is conducted using Microsoft Power BI to support data-driven business decisions in competitive markets, where customer retention is more cost-effective than acquisition. The study focuses on a telecom customer dataset, combining data preprocessing, visual analytics, and predictive modeling to uncover churn patterns and critical risk factors. Through the use of interactive dashboards, stakeholders gain clear, actionable insights into customer behavior and potential churn triggers. The integration of Power BI enables dynamic exploration of data, facilitating a deeper understanding of trends and relationships. This approach effectively bridges the gap between data science and business strategy, demonstrating how visual analytics can transform complex datasets into practical insights. The ultimate objective is to empower organizations with tools to proactively address churn, improve customer loyalty, and enhance overall decision-making. This work underscores the value of combining advanced analytics with intuitive visualization to tackle real-world business challenges.
Authors: Devesh Upadhyay, Ritanshi Jain, Vasudev Sharma, Ishika Pal, Ayush Singhal
Language: English
Subfield: Marketing
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4411291374