🎯 A/B Testing Pro

Professional A/B Testing Tool with ML Predictions, Bayesian Analysis & ROI Calculations

Built for data scientists, growth teams, and anyone who wants to make data-driven decisions with confidence.

✨ Features

📊 Statistical Analysis

• Frequentist Approach: Z-tests, confidence intervals, p-values
• Sample Size Calculator: Power analysis with industry benchmarks
• Effect Size Detection: Cohen's h and practical significance
• Sequential Testing: Early stopping recommendations

🧠 Bayesian Analysis

• Beta-Binomial Model: Prior and posterior distributions
• Probability Calculations: P(B > A) with Monte Carlo simulation
• Expected Loss: Risk assessment for business decisions
• Credible Intervals: Bayesian confidence ranges

🤖 ML-Powered Insights

• Success Prediction: AI estimates test outcome probability
• Industry Benchmarks: Performance comparison by sector
• Risk Assessment: Automated factor analysis
• Optimization Suggestions: Data-driven recommendations

💰 Business Intelligence

• ROI Calculator: Complete financial impact analysis
• Cost-Benefit Analysis: Test investment vs. expected returns
• Payback Period: Time to recoup testing costs
• Annual Projections: Long-term revenue impact

📱 Modern Experience

• Progressive Web App: Install on any device
• Real-time Analytics: Live metrics and updates
• Dark/Light Themes: Customizable interface
• Multi-language Support: English and Russian
• Offline Functionality: Works without internet

📈 Export & Integration

• PDF Reports: Executive-ready analysis documents
• CSV/Excel Export: Raw data for further analysis
• API Integration: Webhook support for automation
• Sharing: Easy collaboration with stakeholders

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🚀 Quick Start

Option 1: Use Online (Recommended)

🌐 Open A/B Testing Pro - No installation required!

Option 2: Run Locally

# Clone the repository
git clone https://github.com/artemxdata/ab-testing-pro.git
cd ab-testing-pro

# Install dependencies
npm install

# Start development server
npm start

# Open http://localhost:3000

Option 3: Install as PWA

1. Visit the live demo
2. Click the install button or use browser's "Add to Home Screen"
3. Use offline anywhere!

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📚 How to Use

1. Planning Your Test

🎯 Set Your Goals
├── Define baseline conversion rate
├── Choose minimum detectable effect
├── Set confidence level (95% recommended)
├── Configure statistical power (80%+)
└── Estimate daily traffic

🤖 Get ML Predictions
├── Industry-specific success probability
├── Expected lift estimation
├── Risk factor analysis
└── Optimization recommendations

2. Analyzing Results

📊 Statistical Analysis
├── Enter conversion data for both groups
├── Review significance tests
├── Check confidence intervals
└── Evaluate effect size

🧠 Bayesian Analysis  
├── Examine P(B > A) probability
├── Review posterior distributions
├── Assess expected loss
└── Make risk-informed decisions

💰 Business Impact
├── Calculate ROI and payback period
├── Project annual revenue impact
├── Evaluate cost-effectiveness
└── Generate executive reports

3. Export and Share

📄 Professional Reports
├── PDF executive summaries
├── Technical documentation
├── Raw data exports
└── API integration payloads

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🧮 Statistical Methods

Sample Size Calculation

n = [Z_α√(2p̂(1-p̂)) + Z_β√(p₁(1-p₁) + p₂(1-p₂))]² / (p₂-p₁)²

Z-Test for Proportions

Z = (p̂₂ - p̂₁) / √[p̂(1-p̂)(1/n₁ + 1/n₂)]

Bayesian Analysis

Posterior: Beta(α + successes, β + failures)
P(B > A) = ∫∫[x>y] Beta(αB, βB) × Beta(αA, βA) dx dy

ROI Calculation

ROI = (Additional Revenue - Test Cost) / Test Cost × 100%

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🛠️ Technology Stack

Category	Technology	Purpose
Frontend	React 18 + TypeScript	Modern UI development
Styling	Tailwind CSS	Utility-first styling
Charts	Recharts	Interactive visualizations
Math	MathJS	Statistical calculations
PWA	Service Workers	Offline functionality
Icons	Lucide React	Beautiful iconography
Export	jsPDF + html2canvas	Report generation
Data	XLSX + PapaParse	File processing

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📁 Project Structure

ab-testing-pro/
├── 📁 public/              # Static assets and PWA files
│   ├── index.html          # Main HTML template
│   ├── manifest.json       # PWA manifest
│   └── sw.js              # Service worker
├── 📁 src/
│   ├── 📁 components/      # React components
│   │   └── ABTestingPro.tsx
│   ├── 📁 hooks/          # Custom React hooks
│   │   └── useABTesting.ts
│   ├── 📁 utils/          # Utility functions
│   │   ├── statistics.ts   # Statistical calculations
│   │   ├── mlPredictions.ts # ML algorithms
│   │   └── exportUtils.ts  # Export functionality
│   ├── 📁 types/          # TypeScript definitions
│   │   └── index.ts
│   ├── App.js             # Main app component
│   ├── index.js           # App entry point
│   └── index.css          # Global styles
├── package.json           # Dependencies and scripts
├── tailwind.config.js     # Tailwind configuration
└── README.md             # This file

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🎨 Key Features Demo

Planning Interface

• Interactive sample size calculator
• Industry-specific benchmarks
• ML-powered success predictions
• Risk assessment matrix

Analysis Dashboard

• Real-time statistical calculations
• Interactive Bayesian visualizations
• ROI and business impact metrics
• Export-ready reports

Advanced Analytics

• Segment analysis and clustering
• Sequential testing recommendations
• Multi-variate test support
• Integration APIs

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🚀 Deployment

GitHub Pages (Current)

npm run deploy

Vercel/Netlify

npm run build
# Upload build/ folder

Docker

FROM node:18-alpine
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
COPY . .
RUN npm run build
EXPOSE 3000
CMD ["npm", "start"]

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🤝 Contributing

We welcome contributions! Here's how to get started:

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

Development Guidelines

• Use TypeScript for type safety
• Follow the existing code style
• Add tests for new features
• Update documentation as needed
• Ensure PWA functionality works

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📊 Performance

Metric	Score	Description
Lighthouse Performance	95+	Optimized loading and rendering
Accessibility	100	WCAG 2.1 AA compliant
Best Practices	100	Security and modern standards
SEO	100	Search engine optimized
PWA	✅	Installable with offline support

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🔮 Roadmap

v2.1 (Next Release)

• Multi-armed bandit algorithms
• Advanced segmentation analysis
• Google Analytics integration
• Team collaboration features

v2.2 (Future)

• Automated test monitoring
• Slack/Teams notifications
• Custom ML model training
• Enterprise SSO support

v3.0 (Vision)

• Real-time test orchestration
• Advanced causal inference
• Marketplace integrations
• No-code test builder

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📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

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🙏 Acknowledgments

• React Team - For the amazing framework
• Tailwind CSS - For the utility-first approach
• Recharts - For beautiful visualizations
• Open Source Community - For inspiration and tools

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📬 Contact & Support

• GitHub Issues: Report bugs or request features
• Email: artemfromspace@outlook@gmail.com

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⭐ If this project helped you, please give it a star! ⭐

Made with ❤️ for the data science community

🚀 Try A/B Testing Pro Now