Digital anthropology as method for lead user identification from unstructured big data

Abstract

This paper focuses on lead user identification in an open data context through the principles of digital anthropology (DA). The approach is demonstrated using a case study from the entertainment industry: the festival of Tomorrowland. Following the principles of DA, the specific data structure of the case selected is studied. This structure follows the tribal roles of Cova and Cova, which are then compared with the lead user characteristics of Belz and Baumbach. The different characteristics and roles are used afterwards to establish the user types that may be found in the big data set of the case study. Unlike earlier methods, such as netnography, which focuses on a specific user type as the main source of insights, our results show that DA requires a change of focus from specific individuals to groups of individuals with the capacity to produce the insights of a lead user. DA shows how all the roles in the data structure present different possibilities for innovation. The application of DA to big data enables the extension of analysis to whole populations instead of specific samples, bringing about new possibilities to model and extract the insights of consumers publicly exposed in the digital media.