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

Does Statsig's custom field targeting work in real-time for event-based experiments?

Statsig provides the capability to target experiments based on user properties, which can include actions users take within an application. When a user performs an action, such as clicking a button, this information can be passed to Statsig as a user property. This property can then be used as a targeting criterion for experiments or feature gates.

To implement this, developers can utilize a 'custom field' as described in the Statsig documentation. This field can be set up to reflect user actions or attributes, enabling real-time targeting based on these criteria.

It is important to note that Statsig operates on the properties of the user that are passed to it, and while it does not store the state of a user, it can act upon the properties provided. For instance, if a 'page_url' property is passed, it can be used to target users who land on a specific page.

Similarly, if an action is taken by the user, such as a button click, this can be communicated to Statsig and used for targeting. For best practices, it is advisable to map different events as different custom fields to avoid overwriting and ensure precise targeting.

For more details on setting up custom fields for targeting, refer to the Statsig documentation on Custom Fields.

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What builders love about us

OpenAI OpenAI
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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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