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⌛ 90-day Pulse expiration

Statsig Product Updates
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5/18/2023
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⌛ 90-day Pulse expiration

As teams have grown their Statsig usage, so has old experiment clutter. A few months back we launched a suite of tooling to manage the lifecycle of your feature flags, and today we’re rolling out automated clean-up logic for old experiments as well.

Starting this week, Statsig will be setting a default Pulse Results compute window of 90 days for all new experiments going forward, after which your Pulse Results will stop being computed. Please note this only applies to experiments, not feature gates, holdouts, or any other config types.

duplicate reviews

You will be able to extend this window at the individual experiment level as you approach the 90-day cap, and your user assignment will not be impacted even if results stop being computed. Read more in our docs.

extended pulse calculation window

In the coming days, experiment owners of impacted experiments will receive an email notification and 14 days to extend the Results compute window, if you wish to. As always, don’t hesitate to reach out if you have any questions- our hope is that this both cleans up your Console and saves teams money long-term!


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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
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