What is decile lift?
Decile lift compares how often leads in the best-scoring tenth of a population convert versus the worst-scoring tenth. A lift of 10x means the top decile converts ten times as often as the bottom.
To calculate it, score a population, sort by score, divide into ten equal groups, then compare conversion rates between groups. The comparison is usually top decile against bottom decile, though top decile against the overall average is also used and produces a smaller number. Which comparison is being quoted should always be stated, because the two are not interchangeable.
Lift is the metric that maps most directly to bidding decisions. If the top band converts far more often than the bottom, there is a concrete argument for paying more for one and less or nothing for the other. That makes it more immediately actionable than aggregate accuracy measures.
Lift is also easy to inflate. A model evaluated on the same data it was trained on will report dramatic lift that disappears in production. Figures worth trusting come from out-of-time validation against outcomes the model did not see during training.
Related terms
- AUC (Area Under the Curve) — AUC measures how well a model separates converters from non-converters across all possible thresholds. 0.5 means no better than chance; 1.0 means perfect separation.
- Conversion propensity — Conversion propensity is a model's estimate of how likely a specific lead is to result in a completed sale or enrollment, usually expressed as a probability or a score derived from one.
- Retrospective validation — Retrospective validation tests a model against historical data where the real outcomes are already known, scoring past leads as if they were new and comparing predictions to what actually happened.