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Split Testing, Bucket Testing

"A/B Testing"

Overview

The Core Concept

A/B Testing (also known as Split Testing) is a user experience research methodology. It consists of a randomized experiment with two variants, A and B. Variant A is the 'Control' (the original version), and Variant B is the 'Challenger' (the version with a change).

Traffic is split evenly between the two versions. By tracking the behavior of visitors on each version, marketers can determine which design, copy, or layout yields a higher Conversion Rate. This is the backbone of data-driven optimization.

Why It Matters

  • Maximizes ROI: Improving a landing page conversion rate from 1% to 2% effectively doubles the return on ad spend (ROAS) without buying more traffic.

  • Mitigates Risk: Instead of redesigning an entire website and hoping it works, A/B testing allows for iterative, safe improvements.

  • Settles Debates: It provides hard data to resolve internal disagreements about design or copy choices.

Key Components

  • Hypothesis: A clear statement predicting what will happen (e.g., "Changing the button color to red will increase clicks by 10%").

  • Sample Size: The number of visitors needed to reach statistical validity.

  • Duration: Tests must run long enough to account for weekly variances (e.g., weekend vs. weekday traffic).

Advanced Strategy Planner

Convert technical theory into professional action plans

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