Winsorization
Apply winsorization in Statsig Warehouse Native to cap extreme metric values at chosen percentiles, stabilizing experiment scorecards against outliers.
Winsorization is a common technique for removing noise in experiment results, specifically from outliers. It works by measuring the percentile Px of a metric and setting all values over Px to Px.
Statsig computes the Px value using all non-zero and non-null unit-level values of the metric; metrics are aggregated from rows or events, and then the Px'th unit's value is used as the threshold to adjust other units' values.
At Statsig, the default percentile for winsorization is 99.9%. This reduces the influence of extreme outliers caused by factors such as logging errors or bad actors.
Statsig applies winsorization to sum, event count, mean, ratio, and funnel metrics, including imported metrics. Statsig doesn't apply winsorization to Participation or User Accounting metrics.
Metric capping
Metric capping is an effective technique for handling outliers. You can define maximum values for a metric for any unit type configured for that metric. Statsig automatically adjusts any value exceeding the cap downward to the cap value.
For example, if purchases greater than $10,000 per day shouldn't skew analysis, Statsig adjusts any transaction exceeding that threshold downward to the limit. Metric capping supports Event Count and Aggregation (sum) metric types.
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