Who is involved in this evaluation?
Policy Researchers, some Data Scientists, and/or Economists
AI Engineers
Apply evaluation methods with the proper measurement tools
Ensure that the product functions as expected throughout the evaluation phase
Key Motivation
Policy makers, donors, and governments require credible evidence before they invest in scaling a solution. Level 4 evaluation is critical because:
Why is this level of evaluation important?
The central reason to do an IE is to inform policymakers, donors and implementers on whether and how to incorporate an intervention in their plans. By isolating the intervention from other influences, impact evaluation enables causal attribution of outcome changes. Once effectiveness is established for a specific setting and population, additional evaluations can test whether it works elsewhere or for other groups. Moreover, since impact evaluations isolate causal effects, they are ideal for measuring unintended (as well as intended) impacts of an intervention.
For many funders and public sector partners, IEs are central to decision-making. They seek credible evidence that a product improves lives—beyond engagement metrics or self-reports—before scaling. A well-designed IE signals real-world effectiveness and the likelihood of meaningful social returns (see e.g. Hauser et al., 2025; UK GOV, 2025).
IEs also help funders compare options. Combined with cost data, they enable cost-effectiveness and cost-benefit analysis—critical when governments, donors, and multilaterals allocate scarce resources. In many cases, IE results directly inform decisions to scale, replicate, or exit.
Note: This playbook can be used directly with AI tools like Claude, ChatGPT, and NotebookLM. Explore how >
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