To measure the impact and Return-On-Investment (ROI) of the Treatment if it launched to 100%. To reduce risk by minimizing damage and cost to users and business during an experiment (i.e., when there is a negative impact). To learn about users’ reactions, ideally by segments, to identify potential bugs, and to inform future plans.
