Visualize how CUPED adjusts experiment results with Datadog

Datadog Experiments introduces a CUPED adjustments visualization that explains why CUPED-adjusted experiment lift can differ from raw lift by breaking the change into individual covariate contributions. CUPED uses pre-exposure metrics and assignment properties to reduce variance and improve confidence intervals, but its adjustments can also alter the estimated treatment effect in ways that are difficult to interpret without additional context. Available from a CUPED-enabled metric’s analysis menu, the visualization presents raw and adjusted relative lift, estimated experiment run-time reduction, and a waterfall showing how each metric lookback or subject property raises or lowers the result. This helps users identify whether a difference is driven mainly by one covariate or several smaller ones, while clarifying that covariate adjustments account for observed imbalances rather than demonstrating causal effects.

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