This paper provides an economic perspective on data-driven innovation in digital products, focusing on the role of complex experiments in measuring and improving social impact. The discussion highlights how tools and insights from economics contribute to each stage of the innovation process. Key contributions include identifying problems, developing theoretical frameworks, translating goals into measurable outcomes, analyzing historical data, and estimating counterfactual outcomes. The paper also surveys recently developed tools designed to address challenges in designing and analyzing data from complex experiments.
