Integrating multiple recommendation schemes for designing sales force support system: a travel agency example

Abstract

This paper proposes a design of sales force support (SFS) system with business intelligence methodologies. OLAP provides embedded multi-dimensional aggregation knowledge. DM provides sequentially associated relationship knowledge. The integration of both should make the support system easier to get accepted by salespersons and helpful for them to conduct customer recommendation and self-management. Different from most recommendation systems mainly concerned with customers as the users, the proposed design of SFS is concerned with salespersons as the major users. It provides various functions by integrating multiple recommendation schemes, such as personal recommendation (based on OLAP), as well as forward recommendation and backward recommendation (based on sequential pattern discovery in DM). The design can hopefully resolve the usage motivation problem which is usually the major critical success factor of CRM, as indicated in the literature. The SFS implementation with enhanced user interface should hopefully stimulate better sales and customer/management satisfaction.