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

Can two landing page type of experiments run simultaneously with different layerIDs?

Yes, it is possible to run two landing page type of experiments simultaneously with different layerIDs. Each experiment will have its own layerID, which allows you to run multiple experiments without needing to update the code on the website for each experiment.

The first experiment can run on the landing page, and the second experiment can run on the ThankYou page. Even though the flow from the landing page leads to the ThankYou page, the two experiments are independent because they have different layerIDs.

The code for setting up these experiments is as follows:

<script  src="[API_KEY]&layerid=[LAYER_NAME]"> </script>

Remember to replace [API_KEY] and [LAYER_NAME] with your actual API key and the layer name for each experiment. Also, update the script to specify the layerid instead of expid when you run experiments as part of a layer.

However, if you are trying to measure an impact after the thank you page, you probably want both of these experiments to be in the same layer.

Lastly, ensure that the two experiments are not in the same layer, because in that case, you will mutually exclude the same users from each other experiment.

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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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