{"id":31740350,"url":"https://github.com/abinjohn8138-commits/churn-analysis","last_synced_at":"2026-05-05T18:40:23.851Z","repository":{"id":318296621,"uuid":"1070657393","full_name":"abinjohn8138-commits/CHURN-ANALYSIS","owner":"abinjohn8138-commits","description":"This project focuses on analyzing customer churn behavior within a telecommunication company using visual insights. 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The aim is to identify key factors contributing to customer churn and assist in decision-making for customer retention strategies.\n\n##  File Description\n\n* **Screenshot_2025-10-06_152430.png**\n  This image contains a dashboard summarizing various aspects of customer churn using different filters and visualizations.\n\n##  Dashboard Highlights\n\n* **Churn by Gender \u0026 Internet Service**\n  Compares churn rates across genders and types of internet service.\n\n* **Churn by Phone \u0026 Multiple Lines**\n  Evaluates how having a phone service or multiple lines influences churn.\n\n* **Churn by Senior Citizen Status**\n  Displays churn based on age demographics, particularly whether the customer is a senior citizen.\n\n* **Monthly and Total Charges Distribution**\n  Box plots show distribution of charges among customers who churned vs. retained.\n\n* **Gender-Based Pie Chart**\n  Shows churn distribution among female customers.\n\n* **3D Column Chart**\n  Compares total charges and monthly charges against churn status for visual impact.\n\n##  Filters Available\n\n* **Multiple Lines**\n* **Phone Service**\n* **Senior Citizen**\n* **Gender**\n* **Churn**\n* **Total Charges**\n* **Monthly Charges**\n\nThese filters allow users to interactively explore data and identify patterns contributing to churn.\n\n##  Key Insights\n\n* Female and male customers show similar churn trends, but specific factors like \"Internet Service Type\" and \"Monthly Charges\" significantly affect churn.\n* Customers with fiber optic internet show higher churn rates.\n* Senior citizens and customers with higher monthly charges tend to churn more often.\n\n##  Tools Used\n\n* **Microsoft Excel** (or similar spreadsheet tool)\n* Charts: Bar graphs, pie charts, box plots, 3D visualizations\n\n##  Purpose\n\nThis analysis helps:\n\n* Understand customer behavior\n* Identify high-risk segments\n* Develop retention strategies based on data insights\n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabinjohn8138-commits%2Fchurn-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabinjohn8138-commits%2Fchurn-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabinjohn8138-commits%2Fchurn-analysis/lists"}