Proxy Metrics in Experiments
Proxy metrics in experiments are faster, more frequent, and less noisy signals used to make experiment decisions when they are logically and historically linked to a slower downstream KPI.
Key points
- Statsig argues that revenue can be too sparse and noisy to use as the primary decision metric for every experiment, even when it remains the ultimate business KPI [src-031].
- A useful proxy sits up-funnel from the target outcome, fires more often, and has a stable historical correlation with the downstream KPI [src-031].
- Proxy metrics should be less exposed to external shocks such as holidays or marketing pulses and should reduce noise enough to create faster evidence [src-031].
- The article’s example is using clicks on “Add to cart” as a faster signal for purchase conversion when historical analysis supports the relationship [src-031].
- The downstream KPI should not disappear; Statsig recommends keeping it as a guardrail while deciding the experiment on the validated proxy [src-031].
Related entities
Related concepts
Source references
- [src-031] Yuzheng Sun — “Speeding up A/B tests with discipline” (2025-06-24)
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