What is A/B testing conceptually?

< 1 min read

A/B testing is a method of comparing two versions of a feature to see which performs better based on a defined metric.
In my project, we tested two versions of a checkout page — Version A (existing) and Version B (simplified layout).
We split users randomly so each group saw only one version.
Our success metric was conversion rate and cart completion rate.
After two weeks, Version B showed a 9% higher conversion rate.
We also checked statistical significance to ensure the improvement was not random.
Based on results, we rolled out Version B to all users.
Conceptually, A/B testing helps make data-driven product decisions with reduced risk.

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