Segmenting online consumers using K-means cluster analysis

Internet users have several characteristics that differentiate them from other online users, so the aim of this research study is to segregate online consumers into diverse consumers segments on the basis of their online shopping behaviour. In this paper, the diverse stages of the consumer decision making process have been discussed and this study explores only three important phases of consumer behaviour in impacting the pre purchase decision (need recognition, information search and evaluation of alternatives). Data was collected from a well defined sample of 1,014 respondents who had an active internet usage rate. K-Means cluster analysis was used to extract four consumer segments - cognizant techno strivers, conversant appraisers, moderate digital ambivalents and techno savvy impulsive consumers. Classifying consumers into well defined segments can aid marketing in developing a more streamlined and focused consumer targeting process.