https://github.com/abinjohn8138-commits/churn-analysis

This project focuses on analyzing customer churn behavior within a telecommunication company using visual insights. The goal is to understand what factors lead to customer attrition and help the business take proactive steps to retain customers.
https://github.com/abinjohn8138-commits/churn-analysis

colab-notebook data-visualization excel insights jupyter-notebook pandas python

Last synced: about 2 months ago
JSON representation

This project focuses on analyzing customer churn behavior within a telecommunication company using visual insights. The goal is to understand what factors lead to customer attrition and help the business take proactive steps to retain customers.

• Host: GitHub
• URL: https://github.com/abinjohn8138-commits/churn-analysis
• Owner: abinjohn8138-commits
• License: mit
• Created: 2025-10-06T09:03:33.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2025-10-06T10:04:35.000Z (9 months ago)
• Last Synced: 2025-10-06T11:38:21.897Z (9 months ago)
• Topics: colab-notebook, data-visualization, excel, insights, jupyter-notebook, pandas, python
• Language: Jupyter Notebook
• Homepage:
• Size: 734 KB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# CHURN-ANALYSIS

Here's a sample **README** content you can use or adapt for your project based on the churn analysis dashboard shown in the image:

---

#  Churn Analysis of Telecommunication Service

##  Overview

This project presents a visual and interactive analysis of customer churn in a telecommunication service company. The aim is to identify key factors contributing to customer churn and assist in decision-making for customer retention strategies.

##  File Description

* **Screenshot_2025-10-06_152430.png**

  This image contains a dashboard summarizing various aspects of customer churn using different filters and visualizations.

##  Dashboard Highlights

* **Churn by Gender & Internet Service**

  Compares churn rates across genders and types of internet service.

* **Churn by Phone & Multiple Lines**

  Evaluates how having a phone service or multiple lines influences churn.

* **Churn by Senior Citizen Status**

  Displays churn based on age demographics, particularly whether the customer is a senior citizen.

* **Monthly and Total Charges Distribution**

  Box plots show distribution of charges among customers who churned vs. retained.

* **Gender-Based Pie Chart**

  Shows churn distribution among female customers.

* **3D Column Chart**

  Compares total charges and monthly charges against churn status for visual impact.

##  Filters Available

* **Multiple Lines**

* **Phone Service**

* **Senior Citizen**

* **Gender**

* **Churn**

* **Total Charges**

* **Monthly Charges**

These filters allow users to interactively explore data and identify patterns contributing to churn.

##  Key Insights

* Female and male customers show similar churn trends, but specific factors like "Internet Service Type" and "Monthly Charges" significantly affect churn.

* Customers with fiber optic internet show higher churn rates.

* Senior citizens and customers with higher monthly charges tend to churn more often.

##  Tools Used

* **Microsoft Excel** (or similar spreadsheet tool)

* Charts: Bar graphs, pie charts, box plots, 3D visualizations

##  Purpose

This analysis helps:

* Understand customer behavior

* Identify high-risk segments

* Develop retention strategies based on data insights

---