A simple, educational dashboard that teaches startup owners how to track key business metrics using Google Analytics.

🤖 AI Disclaimer: All calculations, metrics, formulas, and educational content in this tutorial are generated by AI. While we strive for accuracy, please verify calculations for your specific use case. Found an inconsistency? Report it on GitHub!

• 🎯 Interactive Tutorial Dashboard: Click on any metric to learn how to track it
• 📚 Comprehensive Instructions: Step-by-step guides for Google Analytics setup
• 📈 Business Metrics: LTV, CAC, ARPU, Conversion Rates, and more
• 📊 Visual Charts: Revenue growth, acquisition channels, conversion funnels
• 🎓 Educational Focus: Learn what to track and how to calculate metrics
• 🚀 Zero Setup: No database, no complex configuration - just run and learn!
• ✅ Mathematically Accurate: All calculations verified and realistic for startups
• 🔗 GA4 Integration Ready: Connect to your own Google Analytics 4 data (see integration guide)

1. Clone the repository:

git clone https://github.com/yourusername/startup-analytics-tutorial.git
cd startup-analytics-tutorial

2. Install dependencies:

pip install -r requirements.txt

3. Run the application:

python run.py

4. Open your browser:

http://localhost:5000

# Build and run with Docker
docker build -t startup-analytics .
docker run -p 5000:5000 startup-analytics

1. Fork this repository
2. Go to Railway.app
3. Connect your GitHub account
4. Deploy from your forked repository
5. Your app will be live at https://your-app.railway.app

1. Fork this repository
2. Go to Render.com
3. Create a new Web Service
4. Connect your GitHub repository
5. Deploy automatically

1. Fork this repository
2. Create a new Heroku app
3. Connect to GitHub
4. Deploy from main branch

1. Create account at PythonAnywhere.com
2. Upload your code
3. Configure web app
4. Deploy

• 👥 User Tracking: How to track website visitors and user behavior
• 🔄 Conversion Funnels: How to measure and optimize conversion rates
• 💰 Business Metrics: How to calculate LTV, CAC, and other key metrics
• 📊 Google Analytics: How to set up GA4 for your startup
• 📈 Data Interpretation: How to read and improve your metrics
• 🎯 Channel Analysis: How to track traffic sources and optimize acquisition

• 🚀 Early-stage startup founders learning analytics
• 📊 Marketing teams wanting to understand metrics
• 🎓 Students studying business analytics
• 💼 Consultants teaching clients about analytics
• 📚 Educational institutions teaching startup metrics

The dashboard displays realistic startup metrics with accurate calculations:

• LTV (Lifetime Value): $400.58 (industry standard Stripe method)
• LTV:CAC Ratio: 3.15:1 (excellent - exceeds 3:1 target)
• ARPU (Average Revenue Per User): $20.83/month
• Conversion Rate: 1.25% (realistic for B2B)
• Retention Rate: 94.8% (consistent with 5.2% churn)
• Channel Attribution: 100% total (45% Organic, 25% Social, 15% Paid, 10% Referrals, 5% Direct)

startup-analytics-tutorial/
├── app/
│   ├── __init__.py              # Simple Flask app
│   └── routes/
│       ├── __init__.py
│       └── routes.py            # Single route for tutorial
├── templates/
│   └── tutorial-dashboard.html  # Interactive tutorial dashboard
├── static/                      # Empty (no static files needed)
├── run.py                       # Application entry point
├── requirements.txt             # Dependencies (just Flask!)
├── .gitignore                   # Git ignore file
├── GA_METRICS_GUIDE.md          # Comprehensive GA metrics guide
├── BUILD_YOUR_OWN_DASHBOARD.md  # Guide for building custom dashboards
├── LINKEDIN_POSTS.md            # Ready-to-use LinkedIn content
├── SLIDE_DECK_CONTENT.md        # Presentation content
└── README.md                    # This file

• Backend: Flask 3.0.0 (Python)
• Frontend: HTML5, CSS3, JavaScript, Chart.js
• Styling: Tailwind CSS
• Charts: Chart.js for data visualization
• Deployment: Ready for any Python hosting platform

• GA_METRICS_GUIDE.md: Comprehensive guide to Google Analytics metrics
• GA4_INTEGRATION_GUIDE.md: Step-by-step guide to connect your own GA4 data
• BUILD_YOUR_OWN_DASHBOARD.md: How to export GA data and build custom dashboards
• TROUBLESHOOTING.md: Common issues and solutions
• LINKEDIN_POSTS.md: Ready-to-use LinkedIn content for promotion
• SLIDE_DECK_CONTENT.md: Professional presentation content

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

This project is open source and available under the MIT License.

• Built for educational purposes
• Designed to help startups understand analytics
• Inspired by the need for simple, actionable analytics education
• All metrics verified for mathematical accuracy and business realism

This entire tutorial dashboard, including all calculations, metrics, formulas, and educational content, has been generated by AI. While we have thoroughly tested and verified the calculations, we encourage users to:

• Verify calculations for their specific business context
• Cross-reference with other reliable sources
• Report any inconsistencies by opening an issue on GitHub

If you discover any calculation errors, inconsistencies, or have suggestions for improvement:

1. Open an issue on GitHub
2. Describe the problem clearly
3. Provide your calculation or expected result
4. Help us improve the tutorial for everyone

🎯 Ready to learn startup analytics? Just run the app and start clicking on metrics!

📊 All calculations are mathematically accurate and based on realistic startup scenarios.

🤖 Remember: This content is AI-generated. Please verify calculations for your specific use case!