Ruby on Rails Experiments installation

  1. Install the gems

    Required

    Add the posthog-ruby and posthog-rails gems to your Gemfile:

    Gemfile
    gem "posthog-ruby"
    gem "posthog-rails"

    Then run:

    Terminal
    bundle install

  2. Generate the initializer

    Required

    Run the install generator to create the PostHog initializer:

    Terminal
    rails generate posthog:install

    This will create config/initializers/posthog.rb with sensible defaults and documentation.

  3. Configure PostHog

    Required

    Update config/initializers/posthog.rb with your project token and host:

    config/initializers/posthog.rb
    PostHog.init do |config|
      config.api_key = '<ph_project_token>'
      config.host = 'https://us.i.posthog.com'
    end

  4. Implement your experiment

    Required

    Experiments run on top of our feature flags. You can define which version of your code runs based on the return value of the feature flag:

    Note: Server-side experiment metrics require you to manually send the feature flag information. See this tutorial for more information.

    experimentFlagValue = posthog.get_feature_flag('your-experiment-feature-flag', 'user distinct id')
    

    if experimentFlagValue == 'test'
        # Do something differently for this user
    else
        # It's a good idea to let control variant always be the default behaviour,
        # so if something goes wrong with flag evaluation, you don't break your app.
    end

  5. Run your experiment

    Required

    Once you've implemented the feature flag in your code, you'll enable it for a target audience by creating a new experiment in the PostHog dashboard.

  6. Next steps

    Recommended

    Now that you're running experiments, continue with the resources below to learn what else Experiments enables within the PostHog platform.

    ResourceDescription
    Creating an experimentHow to create an experiment in PostHog
    Adding experiment codeHow to implement experiments for all platforms
    Statistical significanceUnderstanding when results are meaningful
    Experiment insightsHow to analyze your experiment data
    More tutorialsOther real-world examples and use cases

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