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 create a feature gate or user segment based on a specific event occurrence in Statsig?

In the current setup of Statsig, there is no direct method to create a feature gate or a user segment based on a specific event occurrence. Feature gates and user segments are typically created based on user attributes or conditions.

However, you can log custom events using the Statsig SDK and then analyze these events in the Statsig console. While this doesn't directly influence the feature gate or user segment, it can provide valuable insights into user behavior that can inform your decision-making process.

For a more automated solution, you might consider using the Console API. While it doesn't directly support event-based targeting, it can help streamline the process of checking for specific user attributes in gates or segments.

It's important to note that the Statsig SDKs are designed to be performant, meaning they make bucketing decisions based on rules/config they have, and can’t make async calls to look up state about a user as part of making this decision.

If you need to gate based on a user's state, you would need to manage the state of a user property (for example, isSubscriber?) and pass this along in the user object for the SDK to be able to gate based on this state.

For further questions or more specific assistance, it is recommended to reach out to the Statsig team directly. They may be able to provide more detailed guidance or discuss potential future 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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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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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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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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