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

Can a user be consistently placed in the same experiment group when transitioning from a free to a paid user?

In the scenario where you have two experiments running for two different groups of users (for instance, free users and paid users), and a user transitions from one experiment to another (like from a free user to a paid user), there isn't a direct way to ensure that this user will be placed in the same group (TEST GROUP) in the new experiment. The assignment of users to experiment groups is randomized to maintain the integrity of the experiment results.

However, if you want to maintain consistency in the user experience, you might consider using the Stable ID as the experiment's unit type. This ID persists on the user's device, allowing them to have the same experience across different states (like logged out to logged in, or free to paid). It's important not to change the experiment type midway. If the experiment spans different user states, it's best to stick with the Stable ID.

In addition, we offer a feature called Layers which allows you to ensure experiments are mutually exclusive, and that a user is only assigned to one of the tests within the Layer. We also support “Targeting Gates”, which determines if a user should be allocated to an experiment based on some criteria (ie; targeting paid vs free users).

Once a user is qualified for an experiment, we randomize that user into either Test or Control by default. So it’s possible for a user to be in Test in ExperimentA and Control in experimentB.

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What builders love about us

OpenAI OpenAI
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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.
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.
Karandeep Anand
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.
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.
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.
Partha Sarathi
Director of Engineering
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