Ricardo1826/AnalystLab_Week1_CustomerChurn

Business analytics case study on customer churn for AnalystLab Africa's Data Analytics Internship (Week 1). Junior Data Analyst engagement for ABC Communications Ltd - EDA, visualisations, and business recommendations on the Telco Customer Churn dataset. # AnalystLab Africa — Week 1: Customer Behaviour & Business Performance Analysis **Programme:** AnalystLab Africa — Data Analytics Internship **Author:** Richard GNALOU **Role:** Junior Data Analyst **Client (scenario):** ABC Communications Ltd ## Business Scenario As a Junior Data Analyst at AnalystLab Africa Consulting, this project investigates customer churn for ABC Communications Ltd and provides business insights to support customer retention strategies. ## Dataset Telco Customer Churn Dataset — 7,043 customers, 21 features (demographics, account information, subscribed services, churn status). ## Business Questions 1. What does the customer base look like? 2. Which segments have the highest churn? 3. Does contract type influence retention? 4. Does tenure affect loyalty? 5. Which services influence churn? 6. Which payment methods have higher churn? 7. What actions should management take? ## Repository Structure AnalystLab_Week1_CustomerChurn/ ├── data/ │ └── telco_customer_churn.csv # Raw dataset ├── notebooks/ │ └── customer_churn_analysis.ipynb # Full analysis: Business Understanding, │ # Data Inspection, Business Analysis, │ # Insights & Recommendations (Parts 1-5) ├── presentation/ │ ├── Business_Presentation.pptx # Executive summary slides (EN — official deliverable) │ └── Business_Presentation_FR.pptx # French version (bonus, personal use) ├── dashboard/ │ └── customer_churn_dashboard.pbix # Power BI dashboard (bonus, not required) └── README.md ## Methodology The full analysis — including the Business Understanding Report, Dataset Inspection, Business Data Analysis, Insights, and Recommendations — is contained in a single Jupyter notebook (`notebooks/customer_churn_analysis.ipynb`), organised as follows: 1. **Part 1 — Business Understanding Report:** business context, problem statement, why churn matters, and objectives of the analysis 2. **Part 2 — Data Loading & Inspection:** shape, data types, missing values, duplicates, outlier check, and des …