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

What is the preferred way to bulk query experiments for a large number of users?

The current Statsig SDK does not provide a method for bulk querying experiments for a large number of users in a single call. The getExperiment function is designed to be called for individual users. If you need to get data about all experiments for a specific user ID, you can use the getExperiment function with different user IDs as many times as you want.

Please note that calling getExperiment will trigger an exposure for that user on that day. If they weren’t in a test or control group, they would be exposed and count towards experiment metrics from that day forward.

If you have a use case where you need to know the evaluation but do not want to enroll the user in an experiment group, you can use the getExperimentWithExposureLoggingDisabled API.

To determine if a user has participated in an experiment, you need to download the exposure report for each experiment to see which users have checked it. The daily reports API is an enterprise feature that can be enabled for your project.

If you're using an SDK to evaluate experiments, it should be pretty simple to just iterate through and check for each user. This is the recommended route for handling large numbers of users.

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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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