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 best practice for using one Statsig account for both dev/test and production environments?

Statsig currently supports metrics calculation for a single production environment. If you have multiple environments set up, you will only be able to use one as your production environment for metrics and experiments.

When running an experiment, the default behavior is that the experiment will run in all environments. This means that if you try to access the config values of the experiment, you will get a valid value, even if you are in a non-production environment.

If you want your experiment to only run on production, you can set a targeting gate. This will ensure that only users in the production environment will pass the gate and be included in the experiment.

Here is an example of how you might access the config values of an experiment:

javascript useExperiment(XXX).config.get(YYY, false);

In this example, XXX is the experiment you are running, and YYY is the config value you are trying to access. If the experiment is not running in the current environment, you will get the default fallback value, which is false in this case.

Remember, once you start an experiment, it will run in all environments unless you set a targeting gate to restrict it to specific environments.

The best practice is to use the experiment checklist and diagnostics tab to instrument the test, enable it in lower environments, and validate that exposures are flowing through. Then, when you’ve validated these, you click “Start” to go to production. This workflow is typically adequate for most users.

Please note that this is subject to change as Statsig continues to evolve and add new features. Always refer to the official Statsig documentation for the most up-to-date information.

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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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