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

Can I view raw events for an experiment group in Statsig?

To view raw events for an experiment group in Statsig, you can utilize the Events Explorer feature. This tool is designed to provide you with sample rows for events, which is particularly useful when you need to familiarize yourself with the data schema or wish to observe the exact data being logged.

The Events Explorer operates on a 14-day rolling window of sampled data, which allows for near real-time data availability. It is an excellent resource for identifying trends, making day-to-day or week-to-week comparisons, and gaining a high-level understanding of event occurrences.

However, it is important to recognize that the Events Explorer is not intended for retrieving all data associated with a specific user or for producing a precise count or export of a particular event. For tracking individual user events and exposures, the Users tab should be utilized instead.

Please note that the Events Explorer's sampling approach may not provide a complete dataset for exhaustive analysis but is suitable for general insights and trend monitoring.

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What builders love about us

OpenAI OpenAI
Brex Brex
Notion Notion
SoundCloud SoundCloud
Ancestry Ancestry
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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