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

Why is there cross-contamination in experiment groups and discrepancies in funnel vs summary data?

When conducting experiments, it is crucial to ensure that there is no cross-contamination between control and treatment groups and that data is accurately reflected in both funnel and summary views.

Cross-contamination can occur due to implementation issues, such as a race condition with tracking. This happens when users, particularly those with slower network connections, land on a control page and a page-view event is tracked before the redirect occurs.

To mitigate this, it is recommended to adjust the placement of tracking scripts. The Statsig redirect script should be positioned high in the head of the page, ensuring that it executes as early as possible. Meanwhile, page tracking calls should be made later in the page load lifecycle to reduce the likelihood of premature event tracking. This adjustment is expected to decrease discrepancies in tracking and improve the accuracy of experiment results.

Additionally, it is important to confirm that there are no other entry points to the control URL that could inadvertently affect the experiment's integrity. Ensuring that the experiment originates from the correct page and that redirects are functioning as intended is essential for maintaining the validity of the test.

Lastly, it is necessary to have specific calls in the code to track page views accurately. These measures will help ensure that the experiment data is reliable and that the funnel and summary views are consistent.

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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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