A model of customer relationship management and business intelligence systems for catalogue and online retailers

Authors:
Dien D. Phan;Douglas R. Vogel
Affiliations:
Information Systems Department, St. Cloud State University, St. Cloud, MN 56301, USA;Information Systems Department, City University of Hong Kong, Kowloon Tong, Hong Kong
Venue:
Information and Management
Year:
2010

Citing 4
Cited 6

The case research strategy in studies of information systems

MIS Quarterly
Amazon.com Recommendations: Item-to-Item Collaborative Filtering

IEEE Internet Computing
Segmenting online customers to manage business resources: a study of the impacts of sales channel strategies on consumer preferences

Information and Management
How can the Web help build customer relationships?

Information and Management

Capturing data quality requirements for web applications by means of DQ_WebRE

Proceedings of the 2nd International Workshop on Business intelligencE and the WEB
Analytical customer relationship management in insurance industry using data mining: a case study of Indian insurance company

International Journal of Networking and Virtual Organisations
Exploring the influence of personal schema on trust transfer and switching costs in brick-and-click bookstores

Information and Management
An integrative framework for customer relationship management: towards a systems view

International Journal of Business Information Systems
Capturing data quality requirements for web applications by means of DQ_WebRE

Information Systems Frontiers
An information delivery model for banking business

International Journal of Information Management: The Journal for Information Professionals

Quantified Score

Hi-index	0.00

Visualization

Abstract

As more retailers evolve into customer-centric and segment-based business, business intelligence (BI) and customer relationship management (CRM) systems are playing a key role in achieving and maintaining competitive advantage. For the past ten years, the authors have had the rare opportunity of observing and interviewing employees and managers of three different management teams at three separate Fingerhut companies as they experimented with various ITs for their companies. When the first Fingerhut company peaked in 1998, as many as 200 analysts and 40 statisticians mined the database for insights that helped predict consumer shopping patterns and credit behaviour. Data mining and BI helped Fingerhut spot shopping patterns, bring product offerings to the right customers, and nurture customer relationships. By 1998, Fingerhut was the second largest catalogue retailer in the U.S. with revenues nearing $2 billion. However, after Federated acquired Fingerhut in 1999 and made it a subsidiary, Fingerhut Net, it suffered great losses and was eventually liquidated. Finally, a new company, Fingerhut Direct Marketing, was resurrected in 2002 under a new management team, and it once again became successful. What went right? What went wrong? The paper concludes with CRM and BI systems success factors and a discussion of lessons learned.