Customer Relations Management in Information Systems Research

Customer Relations Management (CRM) involves attracting and keeping “Economically Valuable” customers while repelling and eliminating “Economically Invaluable” ones. CRM involves changing relationships and improving return-on-investment from customer relationships (ROI-CR.) We are experiencing a shift from a transaction-based economy to a relationship-based one (Keen 1999.) Two important business relationship types exist: those between enterprises and customers; and those between and among enterprises (Kalakota 1996.) This paper addresses the former. However, a there is a significant amount of research into traditional “Market Channels” (See (Bowersox 1990; Ganesan 1994; Syed Saad 1996; Cannon 1999; Geyskens 1999) for examples) as well as into eCommerce (EC) Market Channels (See (Kim 1999; Menon 1999; Son 1999)) Recent and upcoming scholarship and professional activities illustrate the importance the IS Research Community places on CRM. This paper presents a framework for IS CRM Research Topics, a discussion of IS CRM scholarly and professional research directions and activities

The MindMine Comment Analysis Tool for Collaborative Attitude Solicitation, Analysis, Sense-Making and Visualization

Artificial Intelligence Lab, Department of MIS, University of ArizonaThis paper describes a study to explore the integration of Group Support Systems (GSS) and Artificial Intelligence (AI) technology to provide solicitation, analytical, visualization and sense-making support for attitudes from large distributed marketing focus groups. The paper describes two experiments and the concomitant evolutionary design and development of an attitude analysis process and the MindMine Comment Analysis Tool. The analysis process circumvents many of the problems associated with traditional data gathering via closed-ended questionnaires and potentially biased interviews by providing support for online free response evaluative comments. MindMine allows teams of raters to analyze comments from any source, including electronic meetings, discussion groups or surveys, whether they are Web-based or same-place. The analysis results are then displayed as visualizations that enable the team quickly to make sense of attitudes reflected in the comment set, which we believe provide richer information and a more detailed understanding of attitudes