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A/B Testing (Statistics)

A randomized experimentation process wherein two or more versions of a variable are shown to different segments of users at the same time to determine which version leaves the maximum impact and drive business metrics.

Categoryai

Overview

A/B testing (or split testing) is the practical application of hypothesis testing in business and product development. It is used to compare two versions of a webpage, app feature, or marketing email to see which one performs better.

The Process

  1. Identify a Goal: (e.g., increase click-through rate).
  2. Create a Variant: (e.g., change the color of a button).
  3. Split Traffic: Randomly assign users to the Control (A) or Variant (B) group.
  4. Collect Data: Measure the performance of both groups.
  5. Analyze Results: Use statistical tests to determine if the difference is significant.

Key Metrics

  • Conversion Rate
  • Click-Through Rate (CTR)
  • Bounce Rate

Related Terms

Hypothesis TestingP-valueCausationRandom Sampling