By default, we use PostHog's multivariate feature flags to evenly assign people to variations (unless you choose to run an experiment without feature flags). The experiment feature flag is initialized automatically when you create your experiment.
In any experiment, there is one control group and up to nine test groups. Each user is randomly assigned to one of these groups based on their distinctId. This assignment is stable, meaning the same user will remain in the same group even across different sessions and devices.
It's important to note that when dealing with low data volumes (less than 1,000 users per variant), the difference in variant exposure can be as much as 20%. This means a test variant could have only 800 people, while the control variant has 1,000. All our calculations take this exposure discrepancy into account.