Data Mining Applications in the Hospitality Industry

Data Mining Applications in the Hospitality Industry

Soo Kim (Montclair State University, USA)
Copyright: © 2009 |Pages: 5
DOI: 10.4018/978-1-60566-010-3.ch064
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Abstract

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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Background

Simply speaking, data mining is the use of the data from the warehouse to discover unpredictable patters, trends and threats through multidimensional analysis or on-line analytical processing, or OLAP (Peacock, 1998; Ross, 1997). The hospitality industry is known as a highly customer-centered business and accumulates large amounts of customer data from central reservation systems (CRS), property management system (PMS), point-of-sale (POS), and guest loyalty program databases. Therefore, data mining application can play a huge role in the hospitality industry (Monash, 2006). The volume of guest information collected via electronic transactions is greater than what humans can easily manage without the aid of technology (Magnini, Honeycutt, & Hodge, 2003). Data-warehousing and data-mining technologies can easily handle large and complex databases and assist hoteliers and restaurateurs in predicting future customers’ behaviors, designing marketing campaigns, supporting market analysis, evaluating and refining loyalty programs, creating strategies, and conducting trends analysis (Buchthal, 2006; Singh & Kasavana, 2005; Magnini, Honeycutt, & Hodge, 2003; Min, Min & Emam, 2002; Rowe, 1999).

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