Data mining for hotel firms: Use and limitations

• Published in: The Cornell hotel and restaurant administration quarterly Vol. 44; no. 2; pp. 94 - 105
• Main Authors: Magnini, Vincent P., Honeycutt, Earl D., Hodge, Sharon K.
• Format: Journal Article
• Language: English
• Published: Ithaca Elsevier Inc 01.04.2003; SAGE PUBLICATIONS, INC
• Subjects: Brand loyalty; Corporate profits; Customers; Data mining; Decision making; Gaming machines; Hospitality industry; Hotels & motels; Hypothesis testing; Information systems; Market strategy; Marketing; Neural networks; Software; Trends; United States > US
• ISSN: 0010-8804; 1938-9655; 1552-3853; 1938-9663
• DOI: 10.1016/S0010-8804(03)90022-X

Data mining is a largely automated process that uses statistical analyses to sift through massive data sets to detect useful, non-obvious, and previously unknown patterns or data trends. The emphasis is on the computer-based exploration of previously uncharted relationships (i.e., using "machine learning" methods that typically require only limited human involvement). Without data mining, valuable marketing insights about customers' characteristics and purchase patterns may remain largely untapped. By uncovering such previously unknown relationships, managers have the potential to develop a winning marketing strategy that increases their hotel's bottom line. Hotel managers understand the importance of adapting to the changing business environment not only to remain competitive, but merely to survive. As a result, technology has become a large and growing expense for many hotel corporations. Under such a technology framework, data mining is a valuable competitive tool being adopted by hotel corporations in an effort to create customer value.