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🎚️ Enhanced WHN Switchback
2/24/2026
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🎚️ Switchback Enhancements for WHN
We rolling out an improved Switchback Experimentation model to WHN customers. The new Switchback experiment utilizes a regression-based analysis method that replaces our previous bootstrapping approach. This update brings greater flexibility and analytical power, including the ability to break down results by pre-computed dimensions, more configurable burn-in/out periods, and improved scheduling and clustering.
What is a Switchback experiment?
By alternating treatments over time for the same units, switchbacks help control for interference and capture more realistic system-level effects. Use a switchback experiment when you can’t reliably randomize at the user level—typically because treatments affect shared systems or environments (e.g., marketplaces, pricing, routing, or infrastructure).
How do I enabled the enhanced features?
Cutting over to the new Switchback model is a breaking change, and we’ll work closely with customers running legacy switchback experiments to plan a smooth migration. For customers who haven’t previously used switchback experiments in Statsig, the feature will be rolled out in the coming days. If you’re interested in learning more or getting started, feel free to reach out via Slack or your account manager.
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