Paper Title
Privacy Preserving Data Mining For Customer Relationship Management

Customer Relationship Management (CRM) not only is a competitive advantage, but also maintaining customers and explaining specific strategies for each client is essential in any business. Substantial growth in hardware and software technology, large amounts of data are generated and stored. As a result, the main problem in CRM is not the lack of information about the customer, but the problem emerges when processing the huge volume of information and translating them into useful knowledge with the aim of improving CRM and creating a long-term and profitable relationship with customers. The huge volume of informationhave provided an excellent bed for the use of data mining techniques so that by applying the knowledge discovery models on this information to create very good knowledge, especially in CRM. No data mining technique can operate without violating the privacy of the data owners. Given that ETL is one of the data mining steps, the focus of preserving privacy is more in data mining algorithms and less attention in ETL is paid to this issue. Thispaper aims at examining solutions proposed for preserving privacy in data mining,especially in the techniques of association rules, which has many applicationsin CRM. In addition, by using the best proposed method and simultaneous use of it and techniques used in preserving privacy in ETL,we have attempted to find a better balance between privacy and the economic benefits. Keywords- Data mining, CRM, Privacy Preserving, ETL, Association Rules