Data Mining Applications in the Hospitality Industry

Data Mining Applications in the Hospitality Industry

Soo Kim (Montclair State University, USA)
DOI: 10.4018/978-1-61520-969-9.ch067


Some people say that “success or failure often depends not only on how well you are able to collect data but also on how well you are able to convert them into knowledge that will help you better manage your business (Wilson, 2001, p. 26).” It is said the $391 billion restaurant industry generates a massive amount of data at each purchase (Wilson, 2001), and once collected, such collected data could be a gigantic tool for profits. In the hospitality industry, knowing your guests in terms of where they are from, how much they spend money, and when and what they spend it can help hospitality managers formulate marketing strategies, enhance guest experiences, increase retention and loyalty and ultimately, maximize profits. Data mining techniques are suitable for profiling hotel and restaurant customers due to their proven ability to create customer value (Magnini, Honeycutt, & Hodge, 2003; Min, Min & Emam, 2002). Furthermore, if the hospitality industry uses such data mining processes as collecting, storing, and processing data, the industry can get strategic competitive edge (Griffin, 1998). Unfortunately, however, the hospitality industry and managers are behind of using such data mining strategies, compared to the retail and grocery industries (Bogardus, 2001; Dev & Olsen, 2000). Therefore, there is a need for learning about such data mining systems for the hospitality industry. The purpose of this paper is to show the applications of data mining systems, to present some successes of the systems, and, in turn, to discuss some benefits from the systems in the hospitality industry.

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