Frequently Asked Questions

A curated summary of the top questions asked on our Slack community, often relating to implementation, functionality, and building better products generally.
Statsig FAQs
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GENERAL

How are users assigned to groups in an experiment, and can their group assignment change over time?

Date of slack thread: 4/18/24

Anonymous: In a given experiment that’s defined by a user ID type: once a user is exposed to that group, will they always be exposed to that group, or can they be exposed to a different group for a later session?

tore (Statsig): I’ll add a bit more info here, since this is a common point of confusion. A lot of times people assume we track all users by their ID to know who is in which group, but that doesn’t scale well. Instead, we make it deterministic: given a stable state of experiment, targeting criteria, and a stable user object, you will get the same evaluation, always.

Rather than switching groups, the more likely thing to happen is that the user is no longer eligible for the experiment (fails the targeting gate). If you aren’t using a targeting gate, you are good to go. If you are, and the user properties change in a way that causes them to fail the targeting gate, a subsequent check could go from bucketed into an experiment group to not eligible for the experiment.

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Why the best build with us

OpenAI OpenAI
Brex Brex
Notion Notion
SoundCloud SoundCloud
Ancestry Ancestry
At OpenAI, we want to iterate as fast as possible. Statsig enables us to grow, scale, and learn efficiently. Integrating experimentation with product analytics and feature flagging has been crucial for quickly understanding and addressing our users' top priorities.
OpenAI
Dave Cummings
Engineering Manager, ChatGPT
Brex's mission is to help businesses move fast. Statsig is now helping our engineers move fast. It has been a game changer to automate the manual lift typical to running experiments and has helped product teams ship the right features to their users quickly.
Brex
Karandeep Anand
President
At Notion, we're continuously learning what our users value and want every team to run experiments to learn more. It’s also critical to maintain speed as a habit. Statsig's experimentation platform enables both this speed and learning for us.
Notion
Mengying Li
Data Science Manager
We evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration. We wanted a complete solution rather than a partial one, including everything from the stats engine to data ingestion.
SoundCloud
Don Browning
SVP, Data & Platform Engineering
We only had so many analysts. Statsig provided the necessary tools to remove the bottleneck. I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig.
Ancestry
Partha Sarathi
Director of Engineering
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