📊 Customer Churn Analysis (Excel-Based Case Study)

📘 Project Overview

This project presents an analytical study of customer churn behavior using Microsoft Excel.
The main objective is to identify patterns and drivers behind customer churn and provide actionable insights to improve customer retention and profitability.

The analysis is performed entirely in Microsoft Excel, leveraging data cleaning tools, formulas, PivotTables, and charts.

📊📉 Dashboard

🧾 Dataset Description

The dataset (Customer_Churn.xlsx) contains detailed customer-level data for a telecom company, including demographics, contract types, service usage, and churn information.

The metadata sheet (Metadata Sheet - Customer Churn.pdf) defines each column and its meaning.

🧮 Methodology

1. Data Preparation

• Loaded and validated the dataset in Excel.
• Cleaned inconsistent data types.
• Checked for missing values and duplicates using Remove Duplicates tool

2. Data Transformation

• Created calculated field:
  • Churn rate (%) by category using PivotTables

3. Exploratory Data Analysis (EDA)

Conducted in Excel using:

• PivotTables to analyze churn distribution by:
  • Churn Reason
  • Age group
  • Data Consumption
  • International Plan
  • Account Length
• PivotCharts for better analysis.
• Conditional formatting to highlight in which state the Churn Rate is the highest.

📈 Insights and Findings

• Unlimited Data Plan users show lower churn, suggesting that data limitations drive dissatisfaction.
• Overall churn rate among customers with International plans is 26.9%, indicating a sizable retention challenge.
• Key churn reasons: Poor support quality, limited website self-service, high pricing, and competitor offers with better devices or speed.

🧰 Tools and Techniques Used

Category	Tools / Features
Data Processing	Microsoft Excel
Data Analysis	PivotTables, formulas
Visualization	PivotCharts, slicers, column and line charts, conditional formatting
Reporting	Excel Dashboard with key churn KPIs and visual breakdowns

🏁 Conclusions

This Excel-based analysis provides a structured approach to understanding telecom customer churn without requiring advanced programming tools. It demonstrates that Excel alone can support robust data cleaning, aggregation, and visualization workflows, suitable for initial churn diagnostics and reporting.

👩‍💻 Author

Alicja Buda 📧 alicjabuda@protonmail.com