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

Does setting a feature flag to "Launched" respect existing app version targeting rules?

Date of slack thread: 4/8/24

Anonymous: Hi! We are trying to clean up all of our in progress feature flags that are actually launched at 100% following the documentation here. Since we are an app, these feature flags are gated on app version. Does “launching” a feature flag (setting the status to “launched”) respect the rules on the feature flag? My concern is I don’t want users on an old app version seeing the new feature that is launched at 100% on a newer app version.

Matt Garnes (Statsig): Hi! For that use case, which is a common and important one, you will need to not use the launch feature and instead you can “mark as permanent” so that you can filter for these and you won’t be notified that it is old/stale when you need to keep it around forever.

It’s definitely a limitation that our “launch” functionality doesn’t let you categorize a gate that is not out to literally 100% but effectively as launched as it will ever be, as such. We will keep this in mind as we evolve our gates lifecycle features!

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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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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.
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Karandeep Anand
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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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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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Partha Sarathi
Director of Engineering
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