Abstract
Consumer behavior analysis is an important part of customer relationship management, the traditional analysis is based on the basic theory of economics, no quantitative studies, the results have certain limitations. In the development of the new technology, data mining technology is a powerful data analysis technique and its application in customer relationship management is getting more and more attention. However, from the point of view of the application layer, data mining and customer relationship management have quite one part is in the field of commercial applications, application in non business areas have great development. In this study, the knowledge of related fields are introduced in detail and analyzes the typical application of data mining technology in the application of customer relationship management system. Combined with project management, provides a project implementation process model based on data mining.
Highlights
Data mining technology is the main tool for customer relationship management
The technology of data mining is from a large amount of data to extract the potential, valuable knowledge, models or rules of the process (Bing, 2006)
Through the research and Analysis on the current data mining, from the engineering point of view, the implementation process of data mining project was determined and the theory of consumer behavior analysis applied to the mining system, according to the actual application and feedback to the theoretical research, perfect theory
Summary
The technology of data mining is from a large amount of data to extract the potential, valuable knowledge, models or rules of the process (Bing, 2006). It combines the database, artificial intelligence, machine learning, theory and technology of Cheung et al (2001) in many fields such as statistics. Through the research and Analysis on the current data mining, from the engineering point of view, the implementation process of data mining project was determined and the theory of consumer behavior analysis applied to the mining system, according to the actual application and feedback to the theoretical research, perfect theory. To improve the appropriate implementation of the traditional clustering algorithm in the process of mining projects, improve the efficiency of mining
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
