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 is there a sudden spike in the `new_dau` metric without an expected traffic increase?

When encountering an unexpected spike in the new_dau metric without a corresponding increase in website traffic, there are several potential causes to consider. Firstly, it is important to verify the accuracy and consistency of event logging. Any discrepancies in how events are logged can lead to anomalies in the metrics.

Secondly, if data is being imported from external sources, ensure that the ingestion process is functioning correctly and that data is imported in a timely manner.

Additionally, be aware of timezone differences that may affect the interpretation of metrics; Statsig uses Pacific Standard Time (PST) as its default, which could lead to discrepancies if other systems are set to different timezones.

Lastly, the use of user identifiers should be consistent across all events and sessions to maintain the integrity of the data.

If these checks do not resolve the issue, further investigation into specific events that correlate with the metric increase may be necessary. It is also advisable to reach out directly for support if the cause of the spike remains unclear.

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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
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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.
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
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