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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
TROUBLESHOOTING EXPERIMENTS

Why is the Success Event not being counted on the Autotune Pulse Results?

If you're running an Autotune experiment and notice that the Success Event is not being counted on the Pulse Results, it could be due to a few reasons.

Firstly, ensure that the events you're sending include the same identifier (either userID or stableID) as the one used in your client SDKs for the experiment. This is crucial for Statsig to join the events with the correct experiment groups.

If you're still not seeing the expected results, you might want to check your query history for the user to understand which data is being pulled, and if queries are not executing or are failing. If data is loading, it's likely we're just processing. For new metrics, give it a day to catch. If data isn't loaded after a day or two, please check in with us. The most common reason for metrics catalog failures is due to id_type mismatches.

In the case of using a Segment event for the success metric, it's important to note that there may be a delay in the Autotune results being updated. Data should be updated hourly but could be a bit later depending on your attribution window.

If you continue to not see the data as expected after more time has passed, please reach out for further 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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Mengying Li
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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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Don Browning
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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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