The AB Test block allows you to split the path in 2 randomly. It’s a great way to test the performance of 2 different paths and optimize your bot’s conversion rates.
AB Test block

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Configuration Options

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Traffic Split Percentage

  • A Path Percent: Set the percentage of users (0-100%) who will follow path A
  • B Path Percent: Remaining users automatically follow path B
  • Variable Support: The percentage field supports variables for dynamic testing
  • Validation: Percentage must be between 0 and 100

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Features

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Random Distribution

  • Users are randomly assigned to path A or B based on the configured percentage
  • Distribution is calculated per user session to ensure consistent experience
  • Perfect for A/B testing different conversation flows, messages, or features

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Performance Tracking

  • Monitor conversion rates for each path through your analytics
  • Compare user engagement between different approaches
  • Make data-driven decisions about your bot’s flow

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Advanced Features

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Dynamic Percentage Control

Use variables to control the A/B split percentage programmatically:
  • Set percentage based on user characteristics
  • Adjust split ratios based on time of day or other conditions
  • Implement gradual rollouts by changing percentage over time

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Multiple Path Testing

You can stack multiple AB test blocks to create more complex testing scenarios:
AB Test block multiple paths
This approach allows you to:
  • Test 3 or more different paths simultaneously
  • Create nested A/B tests for more granular optimization
  • Implement multi-variate testing strategies

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Best Practices

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Test Design

  • Single Variable: Change only one element between paths for clear results
  • Sample Size: Ensure sufficient traffic for statistically significant results
  • Duration: Run tests long enough to account for user behavior variations
  • Clear Goals: Define success metrics before starting the test

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User Experience

  • Consistent Experience: Users should get the same path on return visits
  • Seamless Flow: Both paths should provide equal value to users
  • Fallback Strategy: Ensure both paths handle edge cases appropriately

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Data Collection

  • Use Set Variable blocks to track which path users take
  • Store test results in variables for analysis
  • Set up proper analytics to measure conversion rates

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Troubleshooting

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Common Issues

  • Uneven Distribution: Verify percentage settings add up correctly
  • Variable Conflicts: Ensure percentage variables contain valid numeric values
  • Path Isolation: Make sure both paths are completely independent

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Testing Your Setup

  • Use preview mode to verify both paths work correctly
  • Test with different percentage values to confirm distribution
  • Monitor initial results to ensure proper randomization

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Integration Problems

  • Check that downstream blocks handle both paths appropriately
  • Verify variable scoping doesn’t cause conflicts between paths
  • Ensure error handling works consistently on both paths