Making Meaningful User Segments from Datasets Using Product Dissemination and Product Impact
As paper-based personas move to interactive persona analytics systems, online companies face large user populations, making segmentation a daunting exercise, along with creating actionable data-driven personas from these large datasets. In this research, we demonstrate an approach that facilitates user segmentation. The approach leverages product dissemination and product impact metrics with normalized Shannon entropy.