Lesson 7: Target Audience
You can set up your experiment to target a specific group of users, defined by what's called the target audience of your test. The users you target are the users you learn about and you need to consider the population of your experiment when you interpret the results and try to generalize them.
When you set up an experiment, you often want to test your new feature or change on a specific group of users—such as new users, users in certain markets, or users on certain platforms. The group you want to include in your experiment is called targeting population or Audience.
The users you target are the users you learn about
The hypothesis you formulated in the planning phase should describe what users you want to target with your test. It's important to think about that the only group of users you can draw conclusions about is the group of users that you include in your experiment.
For example, the results of an experiment that targets the iOS app are not directly transferable to the Android app. Similarly, the results from an experiment run on users in Brazil don't directly generalize to, for example, users in Germany. Likewise, the results from an experiment on users visiting a particular page in your app is not directly transferable to all your users. This may sound obvious, but sometimes the situation may be a little less obvious. You need to consider the population of your experiment when you interpret the results.
What you can target on
Inclusion criteria can flexibly define the target audience of the test based on attributes. You can pass in any information you want when resolving a feature flag. Any information that you pass in can be used as an inclusion criterion for your experiment. For example, if you pass in country or device type, these can be used to create inclusion criteria.
In Confidence, the connection between your product and the experiment is via feature flags. When you resolve a feature flag in your code, you pass in context attributes that Confidence can use for targeting. For any feature flag with usage, Confidence provides autocomplete with the attributes that have been available in those contexts in the Audience section of the experiment setup page. If you don't know what exists in your evaluation context, the person who added the feature flag to the code probably does.