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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
EXPERIMENTS TROUBLESHOOTING

Why is there a discrepancy between experiment allocation counts and server side pageview metric counts?

The discrepancy between the experiment allocation counts and the ssr_search_results_page_view (dau) counts could be due to several reasons:

1. **User Activity**: Not all users who are allocated to an experiment will trigger the ssr_search_results_page_view event. Some users might not reach the page that triggers this event, leading to a lower count for the event compared to the allocation.

2. **Event Logging**: There might be issues with the event logging. Ensure that the statsig.logEvent() function is being called correctly and that there are no errors preventing the event from being logged.

3. **Timing of Allocation and Event Logging**: If the event is logged before the user is allocated to the experiment, the event might not be associated with the experiment. Ensure that the allocation happens before the event logging.

4. **Multiple Page Views**: If a user visits the page multiple times in a day, they will be counted once in the allocation but multiple times in the ssr_search_results_page_view event.

If you've checked these potential issues and the discrepancy still exists, it might be a good idea to reach out to the Statsig team for further assistance.

Another possible reason for the discrepancy could be latency. If there is a significant delay between the experiment allocation and the event logging, users might abandon the page before the event is logged. This could lead to a lower count for the ssr_search_results_page_view event compared to the allocation.

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What builders love about us

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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.
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Dave Cummings
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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.
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Karandeep Anand
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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.
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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.
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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.
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Partha Sarathi
Director of Engineering
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