Design And Implementation Of CRM Based On Data Mining In The Hotel Management Systems

As a pillar of the tertiary industry, hotel industry is developing rapidly with China's booming economy and enthusiasm for tourist development. Nevertheless, it is also challenged furiously by competitors both at home and abroad. In the era of information explosion, more and more hotels turn to information management to realize competitive advantages with better service, greater efficiency and lower costs.The current hotel management systems have found wide application in all aspects of hotel management, covering front-reception, background financial processing and materials procurement, which have met basic demands of daily management of the hotel. With the promotion of informationization process of the hotel, its business data has shown explosive growth, however, those data and information have not been exploited and utilized in an effective way .The management deals with the hotel business data in a far more limited way, such as data collection, storage and statistics, which only provides surficial and routine information and cannot satisfy requirements of the current marketing strategy of "customer-centric". CRM—customer relationship management, as a new management concept, is being accepted, but its technical implemetation, especially its organic combination with the hotel management system is still in the initial stage,Based on the conventional hotel management system and the theory of CRM and with the help of data warehouse and data mining technology, the thesis tends to extract useful information from existing business data in hotels and establish the model of customer segmentation, which is supportive in comprehensive data analysis by policy makers according to various themes to truly achieve "customer-centric", to raise hotel service levels, and, evantually, to enhance hotel's core competitiveness. Through the summary of a large number of historical data, information of valuable customers has been located and reflected in the daily business flow, which helps directly in decision making. The main work and achievements are as follows:1. Based on the investigation and research in hotel business procedure, the thesis analyzes characteristics of the hotel customers and information related builds a data warehouse and sets up a model of star-cube data collection which extracts and analyzes data through rotating, slicing, cutting and drilling techniques from different angles.2. The thesis uses AHP methods to analyze and calculate customer valu.By doing so, the hotel learns about different customer value in profit realization, finds and maintains high-value customers. By focusing on the development of customers who have potential value with a statistics support for customer segmentation, the hotel further enhances its profitability.3. The thesis uses the ID3 decision-making tree algorithm in the data mining to establish the classification model to describe the specific characteristics of important customers and obtain the general model of important customers. In addition to guidance in decision-making, this model is also effective in new customer prediction.4. The thesis mines data on customer satisfaction with Fuzzy C-means clustering algorithm to obtain the results of the cluster on the degree of the customer's concern about the factors such as satisfaction, therefore, to help the hotel improve customer service by finding out service elements which draw great custmer attention.Around the above contents, this thesis introduces the research and development of CRM theory and data mining technology, as well as the methods and processes of the establishment of data storage. The thesis focuses on the design and application of CRM based on data mining in the GZ hotel management systems, which is meaningful both in CRM application in hotel management and data minging technology implemetation in hotel CRM research.