engleski

UPRAVLJANJE WEB KOMUNIKACIJOM U HOTELSKOM MARKETINGU

All businesses have recognized the importance and significance of creating, maintaining and using databases of their guests, clients, customers and other consumers of their products or ser-vices. The methodology used in collecting data has changed and developed parallel with the development and application of information and communication technologies. The transformation of data collection from the manual method to the use of technology and the Web has helped to facilitate the collection of large quantities of per-sonal data concerning the consumers of products or services. As a result, hoteliers and other actors on the supply side are faced with an enormous quantity of unstructured, mostly transactional, data collected via the Web. A methodology known as data mining has emerged in response to this problem. Data mining refers to a process of searching for and using valuable data which ho-teliers can take advantage of in their one-to-one marketing strategy. Recent studies show that future service consumers rely more on the per-sonal experiences of current consumers than on conventional advertising methods. The reason for this lies in the emotional experiences of individu-als in a hospitality facility or tourist destination. While, on the one hand, the daily comments of past service consumers posted on social networks may provide hoteliers with a promotional oppor- tunity to attract future service consumers, on the other hand, they can represent a real threat by dissuading future service consumers. Today’s blogs represent an enormous source of highly valued data with a relatively high dose of credi-bility. When writing blogs, people reveal them-selves and their experiences which are in most cases imbued with personal feelings, giving them a higher level of persuasiveness. Based on the research problem, the basic hypothesis of this paper can be formulated, which reads: Web data mining provides a better approach to using guest databases and enables more-effective personaliza-tion in identifying the needs, wants and habits of guests as future service consumers.

social network marketing, data mining, web data

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