What is A/B testing?

A/B testing is a method of comparing two or more versions of a product to determine which one performs better on given metrics. Its goal is to make decisions based on data, not assumptions.

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#How it works

1. Two (or more) variants are created

• Variant A is the current (control) version.
• Variant B is the modified (experimental) version. For example: different button text, a different screen design, or a different recommendation algorithm.

2. The audience is split randomly Each user sees only one of the variants. This rules out the human factor and makes the results objective.
3. Data is collected Metrics are tracked: clicks, sign-ups, purchases, retention, conversion, and so on.
4. Comparison and analysis Statistics are used to determine whether there is a significant difference between the variants. The winning variant is rolled out to the main version.

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#Where it's used

• UI/UX - buttons, text, colors, element placement.
• Marketing - email subject lines, banners, pages.
• Product decisions - pricing, recommendations, new features.

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#Important

• The test runs until statistical significance is reached (not based on "gut feeling").
• Parameters cannot be changed during the test, this distorts the result.
• The goal must be clearly defined in advance (for example, "increase sign-ups by 5%").

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#Conclusion

A/B testing is a tool for testing hypotheses that helps understand what actually works for users and make decisions based on facts, not intuition.