Hugo A/B Testing

Motivation

A/B testing is a powerful technique for optimizing web experiences by comparing two versions of a webpage to determine which performs better. This Hugo A/B testing implementation provides a robust, flexible solution for:

• Data-Driven Decision Making: Move beyond guesswork to make informed design and content choices
• Continuous Improvement: Systematically refine website performance
• User Experience Optimization: Understand what resonates with your audience

How It Works

Our Hugo A/B testing solution leverages Hugo's output formats and template system to create multiple page variants:

# Key Configuration Concept
outputs:
  home:
    - HTML      # Control Version
    - TESTHTML  # Test Version

Key Components

• Multiple Output Formats: Generate different page versions
• Flexible Templates: Create distinct variants
• Verification Script: Ensure correct implementation

Getting Started

Prerequisites

• Hugo (Extended Version Recommended)
• Basic understanding of Hugo templating

Installation Steps

1. Clone the repository
2. Configure output formats in config.yaml
3. Create variant templates
4. Run verification script

# Verify AB Testing Configuration
.bin/verify

Best Practices

• Focus on One Variable: Change only one element at a time
• Statistical Significance: Collect enough data
• Clear Hypothesis: Define expected outcomes
• Consistent Metrics: Use standardized measurement

Potential Enhancements

1. Analytics Integration

   <script>
     // Track A/B Test Variant
     window.abVersion = '{{ .OutputFormat.Name }}';
   </script>

2. Randomized Variant Selection

   {{ $variants := slice "index.html" "index.testhtml.html" }}
   {{ $selectedVariant := index $variants (mod (now.Unix) (len $variants)) }}

3. Persistent User Experience

   • Maintain consistent variant for individual users
   • Use cookies for variant assignment

Analyzing Results

Metrics to Consider

• Conversion Rate
• Time on Page
• Bounce Rate
• User Engagement

Recommended Tools

• Google Analytics
• Hugo-compatible tracking scripts
• Custom analytics integrations

Contributing

Contributions are welcomed.

License

This project is licensed under the MIT License.

Support

For questions or support, please create an issue in the repository.

This README provides an overview of the Hugo A/B testing implementation, including the motivation, how it works, key components, best practices, and potential enhancements. The project structure and example code files are also provided for easy reference.