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 I run feature gates within existing experiments and add new features to a variant?

Yes, it is possible to run feature gates within existing experiments. You can add new features to a variant by creating a feature gate that only passes for users who are in that variant. However, it's important to note that adding new features to a variant while an experiment is running could potentially impact the interpretation of the experiment results. Therefore, it's generally recommended to plan your experiment design carefully before starting the experiment to avoid making changes midway.

If you need to run multiple experiments or add new features, you might want to consider using layers. Layers are a powerful way to run many experiments in sequence, one building on top of the learning from the other. This could be a solution for running multiple experiments on the same users without having to change code.

Remember, once you start an experiment, it will run in all environments unless you set a targeting gate to restrict it to specific environments.

If you want to change the behavior of a variant, the recommended approach is to start a new experiment that is a vs. the new variant with the new feature being part of the new variant.

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What builders love about 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.
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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