This step ensures projects begin with clear expectations around sampling, feasibility, and cost—before programming or piloting begins.

Piloting reveals common issues that fully DIY platforms often leave undetected—from underpowered designs and unattainable quotas to logic and randomization errors.

This step gives researchers full visibility without taking on full responsibility to manage complex sampling decisions or troubleshoot problems with a survey in the field.
