🍯 Persistent Assignment

🍯Persistent Assignment on Experiments

This is a new SDK feature that makes user bucketing decisions on experiments sticky even in situations they wouldn't have been previously. Users exposed to an experiment are bucketed into Control or Test deterministically (see how); however allocation or targeting changes can cause a user to to be excluded from an experiment after they were exposed to it. Persistent Assignment ensures that users stay bucketed in the experiment even when allocation or targeting changes.

Some scenarios this unlocks

1. You can roll out an experiment to 100% of users for a week, and then drop allocation to 0%. Users exposed to the experiment in that first week will continue to experience the experiment; other users will not.

2. When you target an experiment at set of users (e.g. low engaged users), if the user state changes they usually fall out of the experiment. With Persistent Assignment they will continue to see the experiment (e.g. even if they move from low engaged -> high engaged).

Learn more about Persistent Assignment on Client SDKs, Server SDKs