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Data Mining Application in Customer Relationship Management: Case study in Saipa Yadak Co.

Akbari, Amin | 2011

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 41371 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Salmasi, Naser
  7. Abstract:
  8. One of the most applicable fields in data mining is customer relationship management (CRM). CRM process includes four aspects: Customer identification, Customer attraction, Customer retention, and Customer development. Data mining can be a supportive tool for decision making in each of these CRM aspects. Huge volume of data and information corresponding to CRM that exists in companies' databases, has made sufficient potential for data mining process and discovering hidden knowledge. Importance of concepts like customer needs identification, customer retention, and increasing customer value for companies has made the need to use of data mining techniques more valuable. Saipa Yadak Co., as a part of SAIPA automotive manufacturing group that undertakes after sale services, is interfacing with large volume of data related to customer claims in guarantee period and deeply senses the necessity to use of practical knowledge discovery techniques on this large database. For this reason, we tried in this research to use information about customer claims at company agents in guarantee period in order to provide sufficient knowledge for improving CRM process in all different aspects of that with application of data mining tools. Varied data mining techniques such as clustering, classification, and association rules discovery algorithms have been used in three approaches: identification and segmentation of customers, customer classification and prediction of high cost customers and to discover relations and trends in car defects. According to results of modeling, K-means in clustering techniques and logistic regression and neural networks in classification techniques have better performance than the other techniques
  9. Keywords:
  10. Data Mining ; Customer Relationship Management ; Segmentation ; Classification ; Association Rules ; Guarantee Period

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