📊 Telco Customer Churn Analysis

Advanced Power BI Project

📌 Overview

This project analyzes customer churn for a telecommunications company using an interactive Power BI dashboard.
The objective is to identify factors driving churn, segment high-risk customers, and provide actionable recommendations to improve retention.

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📌 Key Features

• KPIs: Total Customers, Churn Rate, Churned Customers, Retained Customers, Total Revenue
• Filters: Contract Type, Churn Status, Internet Service, Gender, Senior Citizen
• Advanced Feature: Reset Filters button for one-click clearing
• Customer Details Page: Table with interactive filters

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⭐ STAR Method Breakdown

S — Situation

The business was experiencing significant customer churn, impacting revenue and long-term growth. Understanding churn drivers was essential to improve retention.

T — Task

Analyze customer demographics, services, and contract details to uncover churn patterns and actionable insights.

A — Action

• Cleaned and preprocessed the dataset using Power Query
• Created DAX measures (e.g., Churn Rate, Retained Customers, Total Revenue, Tenure Groups)
• Built an interactive Power BI dashboard with KPIs, filters, and business-focused visuals
• Implemented a Reset Filters button for advanced interactivity

R — Result

• Identified Month-to-Month contract customers as the highest churn risk segment
• Found customers with tenure <6 months contribute the largest share of churn
• Observed customers with fewer services churn significantly more
• Enabled stakeholders to filter, explore, and prioritize high-risk segments efficiently

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📊 Dashboards

1️⃣ Churn Analysis

Identifying churn drivers and high-risk customer segments at a glance.

2️⃣ Customer Details

Drilling down into individual customers to support targeted retention actions.

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🔗 Live Preview

(Live Dashboard)

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📌 Project Takeaways

• Strong relationship between contract type, tenure, and churn
• Early intervention is critical for new customers
• Service bundling reduces churn risk
• Power BI dashboards can provide actionable insights quickly to decision-makers

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📊 Tech Stack

• Power Query (Data Cleaning)
• Power BI (Dashboard & Visualizations)
• DAX (KPIs & Measures)
• Excel / CSV (Data Source)

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🏁 Conclusion

This project shows how Power BI can be used to turn raw customer data into clear churn insights, helping businesses focus retention efforts on the customers who matter most.

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👤 Author

Shadan
Data Analyst

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