SYSTEMATIC ONLINE LEAD USER IDENTIFICATION - CASE STUDY FOR ELECTRICAL INSTALLATIONS
Editor: Christian Weber, Stephan Husung, Marco CantaMESsa, Gaetano Cascini, Dorian Marjanovic, Srinivasan Venkataraman
Author: Pajo, Sanjin; Vandevenne, Dennis; Duflou, Joost R.
Institution: KU Leuven, Belgium
Section: Design Information and Knowledge Management
Identification of emerging needs and partial solutions is crucial for industries to stay competitive in a fast evolving marketplace. A small subgroup of customers, called lead users have been shown to experience needs before the rest of the marketplace and propensity to find solutions to address those needs. Involvement of lead users in the new product development process leads to attractive and successful new products. In this paper, the authors present a fast lead user identification approach that makes use of data mining, network analysis and machine learning techniques. An implementation of the approach for the micro-blogging site Twitter is described and the results of the effectiveness analysis case in the domain of electrical installations are reported. The implemented methodology points to opportunities in systematic and fast identification of lead users online with additional studies for different domains required to validate the approach.