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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

Can we manually expose users to an experiment in Statsig?

Date of slack thread: 7/3/24

Anonymous: Hi! We’re running an experiment that tests whether receiving a piece of physical media will improve site engagement, and have a predefined list of Test and Control users based on their emails. We are planning on putting all these users into a segment, and then using overrides to assign them to Test or Control.

The issue we have is that users must be exposed to the experiment for their metrics to be counted. We may have users in this segment who do not go to the site, and therefore we are not able to expose them – resulting in an artificially small denominator.

I know this is not a typical use case, but is there any way we can manually expose all the users in a segment to an experiment? Thanks in advance!!

Ryan Musser (Statsig): Hey there <@U077KR7LE10> - yes you can manually expose them using our SDK or API. Are you comfortable coding/running scripts? Depending on your skillset I can help you with this just lmk

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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
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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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Karandeep Anand
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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Mengying Li
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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