PaperHigh credibilityData Mining and Knowledge Discovery 18(1) · Ron Kohavi, Roger Longbotham, Dan Sommerfield, Randal M. Henne · February 1, 2009

Controlled Experiments on the Web: Survey and Practical Guide

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Our summary

The practical guide to online A/B testing: how to split live traffic between variants, reach statistical significance, and avoid the common pitfalls that invalidate a web experiment.

Why it matters

The methodological reference for A/B testing in production — grounding a prompt or model change in real user outcomes rather than offline proxies.

Cited by these methods

🔬 A/B testing in production

Published June 26, 2026

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Qlarify Labs. (2026). Controlled Experiments on the Web: Survey and Practical Guide. Retrieved from https://labs.qlarify.fi/references/controlled-experiments-web-2009