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A/B Testing Design

The A/B Test Framework

An A/B test is a randomized controlled experiment comparing two variants (A = control, B = treatment) to determine which performs better on a defined metric. It is the gold standard for causal inference in product development, marketing, and UX design. The process: (1) Define the hypothesis ('Changing the CTA button from green to orange will increase click-through rate'). (2) Define the primary metric (click-through rate). (3) Calculate the required sample size. (4) Randomly assign users to A or B. (5) Run the test until the sample size is reached. (6) Analyze results using a statistical test (typically a two-proportion z-test or chi-squared test). (7) Make a decision based on the results.

A/B Testing Design

The A/B Test Framework

An A/B test is a randomized controlled experiment comparing two variants (A = control, B = treatment) to determine which performs better on a defined metric. It is the gold standard for causal inference in product development, marketing, and UX design. The process: (1) Define the hypothesis ('Changing the CTA button from green to orange will increase click-through rate'). (2) Define the primary metric (click-through rate). (3) Calculate the required sample size. (4) Randomly assign users to A or B. (5) Run the test until the sample size is reached. (6) Analyze results using a statistical test (typically a two-proportion z-test or chi-squared test). (7) Make a decision based on the results.