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 namedescription(str): Experiment descriptionvariants(List[str]): List of test variantstraffic_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
- Analytics Core - Core analytics engine
- Analytics Dashboards - Analytics dashboards