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Get the research -based the hotel CRM customer data mining

Author: Yi
Tutor: TangPing
School: Guangdong University of Technology
Course: Computer Software and Theory
Keywords: data mining hotel CRM customer acquisition clustering decision tree
CLC: TP311.52
Type: Master's thesis
Year: 2005
Downloads: 401
Quote: 5
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Abstract


CRM (Customer Relationship Management) is a process of managing interaction activity between enterprise and customers. It is a set of advanced ideas, methods and solutions, which can help to find out and lock the best customers, and satisfy their needs and fulfill their wishes effectively on the right prices, the right time, the right way and the good product and service. Because of lacking capacity of discovering useful information which is concealed in data, it is very difficult for enterprises to convert data into knowledge. With the increasing development of data mining technology, enterprises have the possibility to convert data into knowledge by using the valid, unknown and understanding information extracted from huge database. It can provide decision support for enterprises.The substantial increase tendency of our national economy brings great development chance for hotel industry. It is crucial for hotel how to get hold of this opportunity to improve own strength. Undoubtedly implementing CRM based on data mining is an important approach to improve competitive ability in itself.The technology of customer acquisition in the hotel CRM based on data mining is studied in this dissertation. The goal of this dissertation is seeking for an approach to construct a hotel potential customer model. Combining with the item of Guangdong University of Technology-"the CRM system of Junshan hotel", customer acquisition is realized. Customer acquisition is transforming the potential customer into genuine customer. The study contents are described as follows. Firstly, the work of data preparing that involves data cleaning, data extracting, data transforming and data deriving is completed. In addition, the question on how to build data warehouse in hotel CRM is focused. Secondly, we study the classification and clustering technology and compare with existing classification and clustering algorithms. According to algorithm’s accuracy, simplicity and intelligibility, we select k-means algorithm and ID3 decision tree algorithm to build potential customer model, and propose some

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