User data spectrum theory: Collecting, interpreting, and implementing user data in organizations
Sree Nilakanta Associate Professor
Organizations interested in increasing their user experience (UX) capacity lack the tools they need to know how to do so. This dissertation addresses this challenge via three major research efforts: 1) the creation of User Data Spectrum theory and a User Data Spectrum survey for helping organizations better invest resources to grow their UX capacity, 2) a new UX method and model for organizations that want to capitalize on spoken words from end users called Rapid Meaningful Scenarios (RMS), and 3) a recommendation for UX education in response to the current ACM SIGCHI education Living Curriculum initiative. The User Data Spectrum work is based on 30 interviews and 110 survey responses from UX stakeholders across 120 companies. These data informed the theory as well as a factor analysis performed to identify the most relevant items in the User Data Spectrum survey. The Rapid Meaningful Scenarios methodology was developed based on iterative UX experience with a real-world organization and refined to aid UX professionals in creating structured results based on end users' words. The UX education recommendation integrates experience with the HCI curriculum at Iowa State University and curriculum discussions within the SIGCHI community over the past 5 years. The overall contribution of this research is a set of tools that will enable UX professionals and organizations to better strategize how to increase their UX capacity.