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

Why are user clicks on a banner not showing up in Statsig exposure export?

When user interactions with a feature, such as clicks on a banner, are not reflected in the Statsig exposure export, it is important to understand that Statsig exports all exposures without exception. If a user has been exposed to a feature gate, they will be included in the analysis. However, discrepancies can occur for several reasons.

For instance, if the user's attributes have changed post-exposure or if the feature gate rules were modified, the user might not qualify anymore but would still be included in the analysis.

To verify exposures, users can log into the Statsig console, select the feature gate, and click on 'View Pulse'. The 'Cumulative Exposures' panel will display the total exposures, including a breakdown of users exposed to the feature (treatment or Pass group) and users not exposed to the feature (control or Fail group).

If issues persist, it is recommended to utilize the debugging tools provided in the Statsig documentation to understand why a certain user received a specific value. In cases where the problem cannot be resolved, reaching out to the Statsig team for assistance is advised.

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What builders love about us

OpenAI OpenAI
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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.
Dave Cummings
Engineering Manager, ChatGPT
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.
Karandeep Anand
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.
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.
Don Browning
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.
Partha Sarathi
Director of Engineering
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