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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.
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GENERAL

How can we push `holdout_exposure` events to Mixpanel for cohort analysis?

Date of slack thread: 4/5/24

Anonymous: Hello, we would like to create a Mixpanel cohort for the users in our Holdout group. We have toggled event filtering for Holdout Exposures within the Statsig integrations, however this is not appearing in Mixpanel in the same way that it does for statsig::experiment_exposure and statsig::gate_exposure. Please could you advise how we can push our holdout_exposure events to Mixpanel in order to create a cohort for analysis of our holdout group?

Anonymous: We have toggled everything on correctly, so it would be great if a member of the Statsig team could provide further investigation into our account please. There isn’t a specific link to share for an individual experiment, but its within the Runna project. Thanks

Kenny Yi (Statsig): The holdout exposures should be forwarded with the name statsig::holdout_exposure. And it doesn’t appear like there’s any issue with your configuration. I’ll investigate this further.

Kenny Yi (Statsig): Looks like there’s an issue with mapping the event name. It’s being forwarded as a gate_exposure. We’ll get that fixed and let you know!

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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.
OpenAI
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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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President
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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Director of Engineering
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