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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
FEATURE FLAGS GENERAL

Can the default fail allocation for a feature gate be modified in Statsig?

In scenarios where you wish to modify the default behavior of a feature gate in Statsig, which typically fails (returns false) when conditions are not met, there are alternative strategies you can employ.

One approach is to use negation operators within your conditions, such as 'not in' or 'not equal to', to effectively invert the logic of the gate. This allows you to create a condition that passes by default unless specified criteria are met. Another method is to adjust the 'fail' percentage to 100%. By doing so, you ensure that the feature gate fails for all users, effectively reversing the default 'off' state to an 'on' state.

These techniques allow for greater flexibility in controlling feature gate behavior and can be tailored to meet the specific needs of your experiment or feature rollout.

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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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