> ## Documentation Index
> Fetch the complete documentation index at: https://docs2.growthbook.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Guide on using GrowthBook

> This guide outlines everything you need to know as you scale up experimentation at your company. It covers everything from foundational knowledge (“What is an A/B test?”) to advanced topics and common mistakes.

## Introduction

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.

## Contents

* [Fundamentals of AB Testing](/using/fundamentals)
* [Experimentation Best Practices](/using/experimentation-best-practices)
* [Experimentation Common Problems](/using/experimentation-problems)
* [Experimentation As Part of Your Development Process](/using/product-development)
* [Experimenting in GrowthBook](/using/experimenting)
* [GrowthBook Organization Best Practices](/using/growthbook-best-practices)
* [Securing GrowthBook](/using/security)
* [Experimentation Programs](/using/programs)

## 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 [https://www.exp-platform.com/Documents/GuideControlledExperiments.pdf](https://www.exp-platform.com/Documents/GuideControlledExperiments.pdf)