Customer Acquisition & Churn Tracker for Windows

A comprehensive solution to track customer acquisition and churn rates month over month on Windows computers.

• Browser-based: Runs in any modern web browser
• No installation: Simply open the HTML file
• Modern interface: Professional dashboard with interactive charts
• Local storage: Data saved in browser's local storage
• Export functionality: CSV download capabilities

Quick Start:

1. Download application files
2. Double-click index.html
3. Start tracking your metrics

• Native desktop app: Traditional Windows application feel
• SQLite database: Persistent local data storage
• Advanced charts: Professional matplotlib visualizations
• Full data management: Import, export, and backup capabilities

Quick Start:

1. Install Python 3.7+
2. Run: pip install matplotlib numpy
3. Run: python customer_tracker_desktop.py

• Customer Acquisition Rate: % of leads converted to customers
• Cost per Acquisition: Average cost to acquire one customer
• Churn Rate: % of customers lost each month
• Month-over-Month Trends: Visual trend analysis

• Real-time key performance indicators
• Interactive charts and visualizations
• Month-over-month comparison
• Professional data tables

• Local data storage (no cloud dependency)
• CSV export for external analysis
• Data backup and restore capabilities
• Form validation and error handling

Acquisition Rate (%) = (New Customers ÷ Total Leads) × 100

CPA ($) = Total Acquisition Cost ÷ New Customers

Churn Rate (%) = (Churned Customers ÷ Total Customers at Start) × 100

Annual Churn Rate = 1 - (1 - Monthly Churn Rate)^12

• Operating System: Windows 10 or 11
• Web Browser: Chrome, Firefox, Edge, or Safari (for web app)
• Python: 3.7+ (for desktop app)
• Storage: Minimal disk space required
• Internet: Only needed for initial chart library loading

• 100% Local: All data stored on your computer
• No Cloud: No data transmitted to external servers
• Secure: Password-protect your computer for additional security
• Portable: Easy to backup and transfer data

• Enter data consistently each month
• Use YYYY-MM date format (e.g., 2025-01)
• Include all acquisition costs (marketing, sales, overhead)
• Track both voluntary and involuntary churn

• Review trends monthly
• Compare acquisition vs churn rates
• Calculate customer lifetime value
• Monitor cost efficiency over time

• Export data monthly for backup
• Clear browser cache periodically (web app)
• Keep application files updated
• Monitor local storage space

Both applications include sample data to demonstrate functionality:

• 6 months of acquisition data
• 6 months of churn data
• Pre-calculated metrics and charts

1. Setup: Choose and install your preferred application
2. Data Entry: Add your customer acquisition and churn data
3. Analysis: Review dashboard metrics and trends
4. Export: Download data for external analysis
5. Backup: Regular data export for safekeeping

• Charts not loading: Ensure internet connection for initial setup
• Data not saving: Check browser settings for local storage
• Application won't start: Verify all files are in same folder

• Use local web server for better web app performance
• Export data regularly to prevent loss
• Monitor browser storage usage
• Keep Python packages updated (desktop app)

CustomerTracker/
├── index.html              # Web application main file
├── style.css               # Web application styling
├── app.js                  # Web application logic
├── customer_tracker_desktop.py  # Desktop application
├── setup-guide.md          # Detailed setup instructions
├── desktop-app-code.md     # Desktop app source code
└── README.md               # This file

• Version: 1.0
• Release Date: June 2025
• Compatibility: Windows 10/11
• Language: English
• License: Free for personal and commercial use

• Optimize Marketing: Understand which channels work best
• Budget Planning: Allocate resources effectively
• Growth Tracking: Monitor business expansion
• ROI Analysis: Measure marketing return on investment

• Retention Strategy: Identify when customers leave
• Revenue Impact: Understand revenue loss patterns
• Product Improvement: Find areas for enhancement
• Customer Success: Proactive retention efforts