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 I check the number of users passing the targeting gate and seeing variants in my Statsig experiment?

Date of slack thread: 7/1/24

Anonymous: Hi team! I’ve ran this experiment since last Wednesday and we haven’t gotten any metrics data. We have around 319 exposures, however, we are filtering out some markets we don’t want the experiment to be displayed in. Meaning the amount of users seeing the variants is even smaller. How can we query or check out how many total users are passing the targeting gate and seeing any of the variants?

Anonymous: This is what we see on Statsig:

Timothy Chan (Statsig): The 319 number is the total number of users who pass the targeting gate and are being assigned to the experiment. I suggest adding some top-level metrics that all users should be triggering. That would be a good way to confirm that the logging for exposures/metrics is working. In general, you can view targeting gate activity on the Targeting Gate’s diagnostics page: https://console.statsig.com/6hZpXLzyqnReOFXwKmLfck/gates/cash_loan_terms_and_conditions_exp_ug_enabled/diagnostics

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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
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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
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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Partha Sarathi
Director of Engineering
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