Unlocking insights: telecom customer churn analysis with power BI

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.

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Publication Details

Journal
International Journal of Research in Engineering and Innovation
Published
2025-01-01
DOI
https://doi.org/10.36037/ijrei.2025.9309
Primary Topic
Customer churn and segmentation
Type
article
Field-Weighted Citation Impact
0.00
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article

Unlocking insights: telecom customer churn analysis with power BI

Rajeev Jain, Devesh Upadhyay, Ankit Singhal, Virendra Kumar Sharma et al.
International Journal of Research in Engineering and Innovation
Customer churn and segmentation
article

Unlocking insights: telecom customer churn analysis with power BI

Rajeev Jain, Devesh Upadhyay, Ankit Singhal, Virendra Kumar Sharma, Indra Jeet Pal
article en

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.

International Journal of Research in Engineering and InnovationVol. 09(03)
Chaudhary Charan Singh University (IN)
Openalex Percentile: Top 83%
Customer churn and segmentation
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