Learning A/B Testing (video series)

If you're interested in learning about A/B Testing but prefer your education in a more cinematic format, this series of videos from the Firebase YouTube channel might be of interest to you.

This tutorial explains why A/B testing is important, and how to use Remote Config and Analytics within your app to make sure it's ready for running experiments.


  • What is A/B testing?
  • An overview of Remote Config
  • Remote Config and localization
  • An overview of Analytics
  • Planning for A/B testing in a sample app

This tutorial shows you how to use the Firebase console to create, test, and publish your very first experiment.


  • Creating an experiment
  • Understanding variants
  • Defining goals for your experiment
  • Testing your experiment before publishing
  • Starting an experiment for real

This tutorial shows you how to interpret all the experiment results that you'll see for your A/B test in the Firebase console


  • Why do you need to wait?
  • Finding your experiment results
  • Understanding result ranges
  • Interpreting detailed stats
  • Rolling out an experiment winner

A/B testing and Remote Config is great for testing changes inside your app, but Firebase A/B testing lets you test notifications as well.


  • An overview of Firebase Cloud Messaging
  • Creating an experiment in the Notifications composer
  • Analyzing your results
  • Pushing your notification to the rest of your users

Advanced Topics

These two videos cover additional information you might be interested in, after you've created your first A/B test or two.

This view covers how we added Remote Config to a sample iOS app using Swift, and some of the more advanced use cases.


  • Storing Remote Config keys in an enum
  • Properly localizing your strings
  • Implementing a loading screen
  • Abstracting away implementation details
  • Setting images through Remote Config

This video covers some of the most common questions developers typically have after they've run a few A/B tests.


  • Running more than one experiment at once
  • Using Activation Events
  • Analyzing experiment results in BigQuery