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 when they revisit your page.
We achieve this by creating a SHA-1 hash from a combination of the feature flag key and a distinctId, convert the first 15 characters of this hash (in hexadecimal) into a large integer, and then divide this integer by a predefined large constant to normalize it to a float between 0 and 1. If this float is less than a specified threshold percentage, the feature is enabled for the user; otherwise, it is not.
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.