Skip to main content
An audience definition uses:
  • inclusion criteria that decide what units to include
  • allocation that sets the percentage of the included population to run the experiment on
  • a targeting key that specifies they field in the evaluation context to randomize traffic based on
  • exclusivity to control the behavior of the experiment in relation to other experiments, rules, and segments
On this page, you can find more information about exclusivity and overlapping experiments. If you want to read more about inclusion criteria, allocation, and the targeting key, go to the audience page for flags.

​
Randomization

Confidence uses randomization to assign variants to users. To randomize, Confidence needs to know which field in the evaluation context it should take the value from. Read more in the flag documentation.

​
Sticky Assignment

Under advanced options in the audience section you can enable sticky assignments. When you enable sticky assignments, Confidence writes all assignments to a storage that is accessible at resolve time with low latency. Read more about sticky assignment in the flags documentation.

Audience Reference

Deep dive into audience configuration

Define Audience Criteria

Configure targeting criteria

Exclusive Experiments

Set up mutual exclusion

Treatments Reference

Configure experiment variants