A/B Testing and Customer Analytics in Python: A Story-Driven Journey
Foundations of A/B Testing
What is A/B Testing?
A/B testing is a randomized experimental method that enables data-driven decision-making by:
- Testing different variants against each other in real-world conditions
- Using statistical analysis to determine which version performs better
- Establishing causal relationships between changes and outcomes
Key advantages:
- Eliminates guesswork from decision making
- Provides accurate answers quickly
- Enables rapid iteration on ideas
- Establishes clear cause-and-effect relationships
The A/B Testing Process
Hypothesis Development
- Form clear, testable hypotheses about your product or business
- Define measurable outcomes
- Document assumptions and expected results
Experimental Design
- Random assignment of users to groups:
- Control group (A): Current version
- Treatment group (B)…