Targeting

Targeting interventions identify a subset of a population with a different expected response — high-risk patients, eligible-but-not-enrolled families, frequent absentees — and direct an intervention there. The mechanism amplifies marginal effects by concentrating resources where they have the largest impact.

8

Experiments

2

Policy areas

1972–2019

Year span

5 / 8

Positive

When it works

When the population has heterogeneous response to the intervention and the targeting variable is observable. Predictive risk modeling has unlocked targeting in domains (child welfare, hospital readmissions) where it wasn't previously feasible.

Watch out for

Targeting can encode bias. If the model uses historical enforcement data, targeting follows historical enforcement patterns — not actual underlying risk. Validate the target population against ground truth, not just convenience proxies.

Targeting across policy areas

Public Safety· 7 experiments

Public Health· 1 experiment