Meritbarnabas/-Telco-Customer-Churn-Analysis-analystlab-week5

This project is a Business Analytics Case Study completed as part of the AnalystLab Africa Data Analytics Internship Program. # -Telco-Customer-Churn-Analysis-analystlab-week5 This project is a Business Analytics Case Study completed as part of the AnalystLab Africa Data Analytics Internship Program. The goal is to analyze customer data from a telecom company to understand why customers are leaving (churning) and identify key factors that influence customer retention. Using data analysis and visualization, we provide insights and recommendations that can help the business reduce churn and improve customer loyalty. 🎯 Business Problem Telecom companies face a major challenge: customer churn. Losing customers increases business costs and reduces revenue. This analysis answers the following questions: 1.Why are customers leaving the company? 2.Which factors influence customer churn? 3.Which customer groups are at risk? 4.What strategies can reduce churn? 📂 Dataset Information Dataset Source: Telco Customer Churn Dataset (Kaggle) Records: 7,043 customers Features: 21 variables Target Variable: Churn (Yes / No) Key Features Customer demographics (gender, senior citizen, dependents) Account information (contract type, tenure, payment method) Services used (internet service, streaming, tech support) Billing details (monthly charges, total charges) 🧹 Data Preparation The dataset was cleaned and prepared before analysis: Corrected data types for analysis Removed inconsistencies and duplicates Verified target variable (Churn) Ensured data accuracy for visualization 📊 Exploratory Data Analysis (EDA) The analysis includes: Churn distribution analysis Customer segmentation Contract type vs churn Tenure vs churn Monthly charges vs churn Internet service vs churn Payment method vs churn 🔑 Key Insights Overall churn rate is 26.54% Customers on month-to-month contracts are most likely to churn Customers with short tenure are at high risk of leaving Higher monthly charges increase churn probability Fiber optic users show higher churn rates Customers using electronic ch …