📊 Telecom Churn Analysis Dashboard

📊 Project Type: Customer Retention & Churn Prediction

📁 Tools Used: Excel | Power BI | DAX | Power Query

📊 Skills Applied: Data Visualization | Business Intelligence | Customer Analytics | Predictive Analysis | Trend Analysis

📌 Overview

This Power BI dashboard analyzes customer churn patterns in the telecommunications industry using data from Maven Analytics (Kaggle). The goal is to identify key factors driving customer attrition, predict high-risk segments, and provide data-driven insights to improve customer retention strategies.

📌 Key Insights

Churn Rate: 26.54% of customers left the service, impacting revenue.

Revenue Loss: $3.68M in lost revenue due to churn.

Top Churn Factors: Competitor dissatisfaction (45%), pricing issues (17%), and customer experience (16.8%) were key drivers.

Customer Segmentation: Senior citizens and month-to-month contract users showed higher churn risks.

Service Impact: Customers using Fiber Optic internet (40.72% churn rate) were more likely to leave compared to DSL and Cable users.

📌 Tools & Techniques Used

Power BI – Data visualization, interactive dashboards, and report automation

DAX (Data Analysis Expressions) – Custom calculations, KPIs, and performance metrics

Power Query – Data transformation, cleaning, and preprocessing

Excel – Data extraction, manipulation, and analysis

Predictive Analytics & Trend Analysis – Customer behavior forecasting

📌 Dashboard Preview

📌 Interactive Dashboard Preview

📌 Want to See More?

📂 Download the PBIX file here.