A/B Testing and Customer Analytics in Python: A Story-Driven Journey

Arman Hossen
Level Up Coding
Published in
9 min readNov 8, 2024

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
Typical A/B testing process

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)…

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Written by Arman Hossen

Aspiring Software Engineer | Data Science | ML | Big Data | Blogger

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