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Guide on using GrowthBook


In today's data-driven world, businesses of all sizes rely on A/B testing to make data-driven decisions. A/B testing, also known as split testing, has come a long way from a simple tool to optimize websites, and is often used as a powerful tool to determine the impact of any changes to your application. By measuring how your user behavior and engagement changes in a controlled manner, you can determine causally if your hypothesis is correct, and make informed data-driven decisions that improve user experience, increase conversions, and drive growth.

This document is intended to be an open source and continuously updated guide to A/B testing. Whether you're a seasoned expert at running experiments, or just starting out, this book will provide you with the knowledge and skills you need to run a successful A/B testing program, with a specific focus on GrowthBook, an open source feature flagging and A/B testing platform.

In the following chapters, we'll start with an overview of what A/B testing is, and familiarize you with the terms that are commonly used. We'll cover the basics of statistical significance, sample size, and other key concepts that are essential for understanding A/B testing. Next, we'll cover the best practices for running an A/B test, followed by some of the common mistakes and pitfalls that can affect experiment programs. Finally, we'll go beyond individual A/B tests and talk about how to run an experimentation program, and then specifics of how to do this well with GrowthBook.

We hope after reading this guide, you'll understand that A/B testing is a critical tool for determining causal impact of the changes you make, as well as optimizing flows. By making informed data-driven decisions, you can improve user experience, increase conversions, and drive growth. With the open source A/B testing tool, GrowthBook, you have a powerful and flexible platform that can help you run experiments quickly and easily. We hope that this guide will give you the knowledge and skills you need to run a successful A/B testing program and make data-driven decisions. Whether you're a developer, product manager, data scientist, marketer, or business owner, A/B testing can help you achieve your goals and drive growth.


Other resources

At GrowthBook we highly recommended the book: "Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing" by Ron Kohavi, Diane Tang, and Ya Xu. It is available on Amazon or on Ronny's site at