Motivating Human–Agent Interaction: Transferring Insights from Behavioral Marketing to Interface Design

This paper investigates what drives and impedes Net customers to interact with a marketer's websites and, more specifically, with decision support interface systems (DSISs) employed in these sites to assist users when shopping or searching for high-involvement consumer goods.

Abstract

The understanding of consumer interaction with online EC Websites is one of the big current challenges for online marketers. The present paper investigates what drives and impedes Net customers to interact with a marketer's websites and, more specifically, with decision support interface systems (DSISs) employed in these sites to assist users when shopping or searching for high-involvement consumer goods. DSIS are considered as a predecessor or partially already integrator of more elaborated agent systems that may be used in future EC environments. It is shown that the design of today's DSISs is sub-optimal for both marketers and consumers, because it fails to motivate user interaction. One reason for this might be that little effort has been made to transfer the insights from consumer behavior to the design of EC user interfaces. The current paper aims to address this gap by proposing a number of new DSIS design principles, all of which are based on insights from traditional marketing search- and perceived risk theory. The main contribution of this paper is that it proposes a design approach for EC Websites that intuitively "makes the user model available to the user" [Shneiderman and Maes, 36].