Using attitudinal and descriptive database information to understand interactive buyer-seller relationships

The need to increase our understanding of consumer-seller relationships has been touted by both academics and direct marketers. Particularly needed are research efforts designed to provide greater theoretical and practical guidance into understanding buyer-seller relationships by incorporating a variety of disciplines, including consumer behavior, psychology, and sociology. This exploratory study reports the findings of an empirical investigation of the use of relationship-oriented attitudinal data to classify customers for the purpose of building stronger relationships. The results indicate that customers can be segmented by using relationship-oriented attitudinal variables such as trust, commitment, and relationship benefits/bonds. The resulting segments have different customer profiles, and segment membership can be accurately predicted using these profiles.