Mining customer knowledge for tourism new product development and customer relationship management.

post by : Revaz Johana

Liao, S. H., Chen, Y. J., & Deng, M. Y. (2010). Mining customer knowledge for tourism new product development and customer relationship management.Expert Systems with Applications37(6), 4212-4223.

Tourism plays an important part in the contribution to the regional & national economic development.  The objective would be to improve the behavior of the public according to their purchases patterns. It’s important to know how customers are selecting a tourism product. The key to achieve this objective is to stay close to the customer to seek a long-term relationship. The solution to that treated in this article is: data mining. But what is it exactly?

Data mining: Process of discovering customer knowledge through database. Example: patterns, association, changes. Customer knowledge + product & marketing knowledge from research helps: - Tourism supplier - Promotion - Customer relationship management.

The questions asked in this article are: What are the customer’s profiles in the tourism market or can the knowledge of customers be transformed into knowledge assets of the company? The data mining can reveal the knowledge patterns, the rules & knowledge maps to propose a solution to the case firm, which is the Phoenix Tours International, founded in 1957. Taiwan government only opened foreign tourism in 1981 and in 2001 & 2002 they were selected as “the best tourism firm in Asia”. Their main assignment is to develop new product, new destination discovery, place marketing and cooperate with the upper stream supplier in order to extend new product on the market. The tasks for the planning and operation department are, for example, investigate on the future market opportunities, analyze the market situation, cooperate with partners, evaluate if the product is profitable and finally to release the final product on the market through different channels. Theses different factors are challenging to the firm and according to the author of the article, the data mining approach could provide a more active method. The result showed that the key factor considered by the customer when traveling was the security, the agency reputation, the travel style and finally the price. They also divided the questionnaires into five clusters: remote island tour, easy tour, train/bus tour, environmental hygiene and price. The result proved that the company could design a new product by considering environmental hygiene & product with acceptable fee. Concerning the Asia area, they saw a preference for Thai, Buddha temple tour and theme park holiday. Thai travels are really a competitive product in Taiwan, but they work on a low price travel destination, so they need to work on quality and reputation to gain customer loyalty. The customer perceives the value of the firm through the service, the satisfaction. The firm needs to know how to satisfy the customer with its value proposition (the set of benefits/value it promises to deliver to the customer) in order to keep a long-term relationship. After the analysis of the questionnaires, the firm saw that they had to provide free delivery and consulting services to the middle-class customer. Also, the job and education domain are influencing customers, which wasn’t known before the clustering analysis.