THE DYNAMICS OF SEARCH ENGINE MARKETING FOR TOURIST DESTINATIONS

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1 THE DYNAMICS OF SEARCH ENGINE MARKETING FOR TOURIST DESTINATIONS Bing Pan*, Ph.D. Assistant Professor Department of Hospitality and Tourism Management School of Business and Economics College of Charleston, Charleston, SC , USA Telephone: Fax: Zheng Xiang, Ph.D. Assistant Professor School of Merchandising and Hospitality Management University of North Texas, Denton, TX , USA Telephone: Fax: Rob Law, Ph.D. Professor School of Hotel and Tourism Management Hong Kong Polytechnic University, Kowloon, Hong Kong Telephone: Fax: Daniel R. Fesenmaier, Ph.D. Professor and Director National Laboratory for Tourism & ecommerce School of Tourism and Hospitality Management Temple University, Philadelphia, PA 19122, USA Telephone: Fax: *Corresponding Author Keywords: Tourism marketing, search engine marketing, travel information search, destination marketing, Internet. 1

2 Biosketches Bing Pan, Ph.D., is Assistant Professor in the Department of Hospitality and Tourism Management at the College of Charleston in Charleston, South Carolina. His research interests include information technologies in tourism, destination marketing, and search engine marketing. Zheng Xiang, Ph.D., is Assistant Professor in the School of Merchandising and Hospitality management at University of North Texas. His research primarily focuses on travel information search, emergent Internet-based technologies for travel decisions, and the development of marketing information systems for tourism organizations. Rob Law is Professor of Technology Management in the School of Hotel and Tourism Management, Hong Kogn Polytechnic University. His research interests include Management Information Systems, Modeling and Forecasting, Software Engineering, and Computer Assisted Education. Daniel R. Fesenmaier is Professor and Director at the National Laboratory for Tourism & ecommerce, which located in the School for Tourism and Hospitality Management, Temple University; he is also Visiting Fellow at the Institute for Innovation in Business and Social Research, University of Wollongong, Australia. His research interests include models of travel behavior and the role information technology in traveler decisions, destination marketing and the development of travel marketing information systems. 2

3 Acknowledgements The authors would like to acknowledge the anonymous reviewers for their insightful and constructive comments. The support from the School of Hotel and Tourism Management at the Hong Kong Polytechnic University with an international grant (Grant # 1-ZV2D) made the project possible. Additional support came from the Office of Tourism Analysis, Department of Hospitality and Tourism Management, College of Charleston, USA. Kevin Smith in the Office of Tourism Analysis provided thorough copyediting work and Chris Simpson in BlueIon LLC. provided valuable feedbacks for the manuscript. 3

4 THE DYNAMICS OF SEARCH ENGINE MARKETING FOR TOURIST DESTINATIONS Abstract Search engine marketing (SEM) has become an important strategic tool for destinations and tourism organizations to promote and advertise online. Due to the dynamic and constantly evolving relationships among travelers as information searchers, search engines, and the online tourism domain, the authors argued that a new model must be conceived to capture these relationships in order to better inform SEM practices. The goals of this paper are two-fold: 1) to synthesize research related to search engine marketing in tourism and related fields; and, 2) to present a model that describes the evolving dynamics in search engine marketing. The implications of the model for managerial practice and tourism research are discussed. 4

5 THE DYNAMICS OF SEARCH ENGINE MARKETING FOR TOURIST DESTINATIONS Introduction The Internet has redefined the tourism industry in a number of ways (Werthner and Klein 1999). On the demand side, most travelers rely on the Internet to look for information as part of the trip planning effort (TIA 2005, 2008); on the supply side, tourism businesses and organizations have adopted the Internet as one of the primary communication channels for gaining and retaining visitors (Buhalis and Law 2008; Gretzel and Fesenmaier 2000). Search engines have thus become one of the most valuable means for connecting travelers and tourism businesses (Xiang, Wöber, and Fesenmaier 2008). A report by the Travel Industry Association of America indicates that the majority of U.S. travelers use search engines for vacation planning (TIA 2008). Additionally, a study by the Internet research firm Hitwise indicates that the generation of online traffic to hospitality websites has led to a substantial number of bookings (Prescott 2006; Hopkins 2008). For Search Engine Marketing (SEM) in general, advertisers in North America spent US$9.4 billion on search engines in 2006, which represents a 62% increase from their spending in 2005 and a 750% of increase from 2002 (Elliott 2007). Apparently, SEM has emerged as one of the most important strategic tools within the overall Internet marketing effort for tourism destinations in the United States. Search engines not only provide numerous opportunities for tourism destinations and businesses to engage their potential visitors, but also pose many challenges. In SEM, one of the primary objectives for a business is to improve and maintain its ranking as high as possible on Search Engine Result Pages (SERPs). As such, a constant struggle exists between tourism businesses 5

6 and organizations as they compete among themselves and many other information sources for the attention of online consumers who are sifting through the enormous amount of information available online. On the other hand, search engines are modifying and enhancing their algorithms and changing the criteria by which web pages are ranked, in order to fight against search engine abuse and spamming and to provide the most relevant information to users (Lawrence and Giles 1998). Further, travelers are conducting searches with various queries in order to find most relevant information, based on their background knowledge about travel, the destination, and the search engines themselves (Pan and Fesenmaier 2006). Therefore, the interactions and relationships between these players in online travel information search are extremely dynamic, making SEM a moving target. SEM is a relatively new phenomenon; with a few exceptions, research on SEM is limited in both marketing and tourism literature (Pan, Litvin, and O Donnell 2007; Xiang, Gretzel, and Fesenmaier 2009; Xiang, Wöber, and Fesenmaier 2008; Sen 2005; Beckwith 2003; Moran and Hunt 2005; Ho and Liu 2005). Existing studies on search engines are mostly conducted within the computer science and information science fields, which primarily focus on the technical mechanism of search engines as information retrieval systems. The implications of these studies on marketing practices are unclear, especially in the tourism field. Perhaps more importantly, the dynamics in online search have not been well documented, let alone incorporated into SEM practices. A series of important questions remain unanswered, including: How can a destination compete with other similar businesses knowing that they will probably adopt similar online marketing strategies? How does a destination marketing organization (DMO) compete given that search engines are constantly changing their algorithms? On the other hand, online travelers 6

7 might adapt their behaviors based on the evolving search engines and available information online. Thus, it is argued that the development of successful SEM programs for tourism destinations requires a profound understanding of the dynamics among the parties involved in SEM. The goals of this paper are to synthesize the literature related to both SEM in general and for tourism in specific and, ultimately, to propose a conceptual model that delineates and highlights the dialectics in SEM. This model is intended to provide directions for future research as well as to offer basic principles for dynamic SEM. The paper is organized as follows: the next section, Research Background, critically reviews the literature related to the three key actors in SEM, namely search engines in terms of their basic design and functions, online travelers as search engine users, and the online tourism domain. In the third section, a conceptual model is proposed to describe and highlight the dynamic relationships among user behavior, search engines, and the online tourism domain. Finally, the implications for theory and practice are discussed. 7

8 Research Background Search engines came into existence to support the access to the huge amount of information on the Internet by crawling, indexing, retrieving, and representing relevant information for users based upon computer algorithms (Henzinger 2007; Marchionini 1997). In travel and tourism, search engines have become one of the important sources in consumers use of the Internet to access travel products (TIA 2008). Generally, Search Engine Marketing (SEM) is defined as a form of marketing on the Internet that businesses and organizations seek to gain visibility on SERPs through paid or non-paid means (Moran and Hunt 2005). There are many forms of SEM, from paid inclusion to organic optimization (see Table 1). The three major forms are: 1) organic search based techniques, i.e. search engine optimization, which involves employing methods that help improve the ranking of a website when a user types in relevant keywords in a search engine. These include creating an efficient website structure, providing appropriate web content, and managing inbound and outbound links to other sites; 2) paid inclusion, which means paying search engine companies for inclusion of the site in their organic listings; 3) search engine advertising, or paid placement, which implies buying display positions at the paid listing area of a search engine or its content network. Google AdWords and Yahoo! Precision Match are the two most popular programs currently, wherein paid placement listings are shown as Sponsored Links. Table 1. Forms of SEM The phenomenon of searching on the Internet has attracted numerous studies in computer science, information sciences, and human computer interaction with the focus on the technological aspects as well as user behaviors of searching (Brin and Page 1998; Jansen and Spink 2006; 8

9 Pan, B., S.W. Litvin, and H. Goldman. (2006). Real users, real trips, and real queries: An analysis of destination search on a search engine. Annual Conference of Travel and Tourism Research Association (TTRA 2006), at Dublin, Ireland. Pan,B, Z. Xiang, H. Tierney, D.R. Fesenmaier, & R. Law(2010). Assessing the Dynamics of Search Results in Google. ENTER Conference on Information Technology and Tourism (ENTER 2010), at Lugano, Switzerland. Pan, Bing, and D. R. Fesenmaier. (2006). Online Information Search: Vacation Planning Process. Annals of Tourism Research, 33(3): Pearce, P. (1982). The Social Psychology of Tourist Behavior. Oxford: Pergamon Press. Prescott, L. (2006). Hitwise US Travel Report. Available from Rousseau, R. (1999). Daily time series of common single word searches in AltaVista and NorthernLight. Cybermetrics, 2(3):1. Schwartz, B.. (2009). Yahoo to Drop Paid Inclusion Program, Accessed November 29, 2009 from Sen, R. (2005). Optimal search engine marketing strategy. International Journal of Electronic Commerce, 10(1):9-25. Smith, S.L.J. (1994). The tourism product. Annals of Tourism Research, 21(3): Song, H, and SF Witt. (2000). Tourism demand modelling and forecasting: Pergamon Press Inc. Spink, A., B.J. Jansen, D. Wolfram, & T. Saracevic. (2002). From e-sex to e-commerce: Web search changes. Computer, 35(3): Sullivan, D. (2007). How Search Engines Rank Web Pages. Accessed November 29, 2009 from 39

10 Susman, G.I., and R.D. Everd. (1978). An assessement of the scientific merits of action research. Administrative Science Quarterly, 23(4): Tatum, Clifford. (2005). Deconstructing google bombs: A breach of symbolic power of just a goofy prank? Review of Reviewed Item. First Monday, (10), Thurow, S. (2003). Search engine visibility: New Riders. TIA. (2005). Travelers' Use of the Internet. Washington, DC: Travel Industry Association of America.. (2008). Travelers' Use of the Internet. Washington D.C.: Travel Industry Association of America. Urban, GL, F Sultan, and WJ Qualls. (2000). Placing trust at the center of your Internet strategy. Sloan Management Review, 42(1): Vogt, C. A., and D. R. Fesenmaier. (1998). Expanding the functional information search model. Annals of Tourism Research, 25(3): Wang, Y., and D. R Fesenmaier. (2003). Assessing motivation of contribution in online communities: an empirical investigation of an online travel community. Electronic Markets, 13(1): Wang, Y., and D. R. Fesenmaier. (2006). Identifying the Success Factors of Web-Based Marketing Strategy: An Investigation of Convention and Visitors Bureaus in the United States. Journal of Travel Research, 44: Werthner, H., and F. Ricci. (2004). E-commerce and tourism. Communications of the ACM, 17(12):

11 Werthner, Hannes, and S. Klein. (1999). Information technology and tourism: A challenging relationship. New York: Springer. Wöber, K. (2006). Domain specific search engines. In Destination Recommendation Systems: Behavioral Foundations and Applications, edited by D. R. Fesenmaier, K. Wöber and H. Werthner. Wallingford, UK: CABI. Woodside, A.G., and C. Dubelaar. (2002). A general theory of tourism consumption systems: A conceptual framework and an empirical exploration. Journal of Travel Research, 41(2): Xiang, Z., and U. Gretzel. (forthcoming). Role of social media in online travel information search. Tourism Management. Xiang, Z., U. Gretzel, and D. R Fesenmaier. (2009). Semantic representatin of the online tourism domain. Journal of Travel Research, 47(4): Xiang, Z., Y. Hyun, K. Wöber, and D. R Fesenmaier. (2007). Online representation of tourism: an analysis of search engine results from a major search engines. Paper read at 2007 Travel and Tourism Research Association (TTRA) Annual Conference, at Las Vegas, NV. Xiang, Z., and B. Pan. (2009). Travel Queries on Cities in United States: Implications for Search Engine Marketing in Tourism. In Proceedings of the 16th International Conference on Information and Communication Technologies in Tourism - ENTER Amsterdam, Netherland: Springer. Xiang, Z., K. Wöber, and D. R Fesenmaier. (2008). Representation of the online tourism domain in search engines. Journal of Travel Research, 47(2):

12 Paid Listing Paid Listing Organic Listing Figure 1. Google Search Engine Results Page: Keywords new york hotels 42

13 Figure 2. The Search Engine Marketing Triad Model 43

14 Figure 3. The Dynamic Changes of Top Five Websites for Two Queries on Google in One Month 44

15 Table 1. Forms of Search Engine Marketing (Sen 2005) Type Form Explanation Payment Scheme Examples Nonpaid Search Engine Optimization (SEO) The process of improving the quality or quantity of traffic from search engines to a website None paid to search engines SEO practices Google AdWords Paid Placement Bidding on keywords on SERPs Pay-per-click Yahoo! Precision March Paid Contextual Advertising Pay to appear on relevant websites or web pages Pay-per-Click or Pay- per-thousand- impressions Google AdSense Annual subscription fee to Paid Inclusion search engines to be included Pay Yahoo in their indices 45