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Customer Churn Analysis Demo

Interactive demo of the customer churn prediction system with 97% accuracy

Customer Profile Input
Churn Prediction Results

Enter customer details to predict churn risk

Project Insights from EDA

Key Findings

  • • Male customers: 17% churn rate
  • • Female customers: 16% churn rate
  • • Mobile phone users: 13% churn
  • • E-wallet users: Higher churn

Top Features

  • • Tenure (most important)
  • • Number of complaints
  • • Days since last order
  • • Satisfaction score

Technical Stack

  • • Python & Pandas
  • • Scikit-learn
  • • Seaborn & Matplotlib
  • • Feature engineering