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Analytics A/B Testing

A/B testing framework for conducting experiments and measuring the impact of changes in analytics systems.

Overview

The A/B testing framework provides comprehensive experimentation capabilities for analytics systems, allowing you to test different configurations, algorithms, and user experiences.

Core Features

  • Experiment Design: Create and configure A/B tests
  • Statistical Analysis: Built-in statistical significance testing
  • Real-time Monitoring: Track experiment performance in real-time
  • Segmentation: Test different user segments
  • Multi-variate Testing: Support for complex experiment designs

Usage Examples

Basic A/B Test Setup

from recoagent.analytics.ab_testing import ABTestManager

# Create A/B test manager
ab_test_manager = ABTestManager()

# Create experiment
experiment = ab_test_manager.create_experiment(
name="search_algorithm_test",
description="Test new search algorithm vs current",
variants=["control", "treatment"],
traffic_split=0.5
)

# Run experiment
results = ab_test_manager.run_experiment(experiment)

Advanced Experimentation

# Multi-variate testing
mv_experiment = ab_test_manager.create_multi_variate_experiment(
name="ui_optimization",
factors={
"layout": ["current", "new"],
"colors": ["blue", "green"],
"fonts": ["arial", "helvetica"]
}
)

# Run multi-variate test
mv_results = ab_test_manager.run_multi_variate_experiment(mv_experiment)

API Reference

ABTestManager Methods

create_experiment(name: str, description: str, variants: List[str], traffic_split: float) -> Experiment

Create a new A/B test experiment

Parameters:

  • name (str): Experiment name
  • description (str): Experiment description
  • variants (List[str]): List of test variants
  • traffic_split (float): Traffic split ratio

Returns: Experiment object

run_experiment(experiment: Experiment) -> ExperimentResults

Run an A/B test experiment

Parameters:

  • experiment (Experiment): Experiment to run

Returns: ExperimentResults with statistical analysis

See Also