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CRO Glossary

Uplift

The measured increase (or decrease) in a metric caused by a treatment, relative to what would have happened without it.

Uplift is the causal difference an experiment is designed to isolate: the change in a metric that can be attributed specifically to the treatment, as opposed to noise, seasonality, or other factors. It's closely related to effect size, but 'uplift' is typically used specifically to describe an increase, often expressed as a percentage lift over control.

Uplift modeling extends this idea beyond a single average number by trying to predict which individual users or segments respond most positively to a treatment, versus which are indifferent or even respond negatively (sometimes called 'sleeping dogs'). This is more advanced than a simple segment analysis done after the fact, since it's built explicitly to find heterogeneous treatment effects.

A practical example: a promotional email might show an overall uplift of 2% in click-through, but uplift modeling might reveal that the effect is concentrated entirely among lapsed users, with no effect (or a slight negative effect) among currently active users. Understanding uplift at this level helps teams target treatments more precisely rather than rolling them out uniformly to everyone.

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