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

Why are disabled/launched gates still being passed to the stitch integration even though event filtering is turned off?

When a feature gate is set to Launched or Disabled, it will always return the default value (TRUE for Launched, FALSE for Disabled) and stop generating billable exposure events. However, disabling a feature gate will not stop checks against it - it'll just always return false. Removing it from your codebase will stop checks - assuming you don't have any old versions of your code still running anywhere.

If you're still seeing checks after that, it's possible that there might be some instances where the gate is still being referenced. Double-check your codebase to ensure that all references to this gate have been removed. If the issue persists, it is recommended to flag this issue to the Statsig team for further assistance.

In some cases, you might still see exposure events in Stitch for gates you've launched/disabled (and all are presumably False). This could be due to a bug in the system. The Statsig team is always ready to identify and fix such issues.

Please note that fixes for such bugs are usually rolled out promptly and should resolve over a short period of time. However, if you're still not seeing the issue as resolved on your end, it is advisable to reach out to the Statsig team for further investigation and assistance.

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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.
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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.
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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.
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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.
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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.
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