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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
GENERAL

Can I use Statsig to randomize a number with a specific distribution for A/B testing?

For A/B testing with randomized number distributions, Statsig's experiments feature is the recommended approach.

To achieve this, you should create multiple test groups within an experiment. Each user who interacts with your application will be deterministically assigned to one of these test groups based on their user ID, which could be either a stableID or userID.

This assignment ensures that each user consistently experiences the same test group during the experiment. Test groups can be configured with associated parameters, allowing for dynamic control over the behavior and experience of each test group.

This setup enables you to conduct A/B/n experiments where users are evenly distributed across the different configurations you wish to test.

For detailed guidance on configuring your groups and parameters, refer to the official Statsig documentation on creating and managing experiments.

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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.
OpenAI
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.
Brex
Karandeep Anand
CPO
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.
Notion
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.
SoundCloud
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.
Ancestry
Partha Sarathi
Director of Engineering
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