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Table of Contents:

Chapter 1: Introduction
1.1 Background of the Study
1.2 Problem Statement
1.3 Research Questions
1.4 Objectives of the Study
1.5 Significance of the Study
1.6 Scope of the Study
1.7 Limitations of the Study

Chapter 2: Literature Review
2.1 Overview of Data Mining Techniques
2.2 Customer Relationship Management
2.3 Integration of Data Mining in CRM
2.4 Benefits of Data Mining in CRM
2.5 Challenges of Data Mining in CRM

Chapter 3: Research Methodology
3.1 Research Design
3.2 Data Collection Methods
3.3 Data Analysis Techniques
3.4 Sampling Strategy
3.5 Research Ethics

Chapter 4: Discussion of Findings
4.1 Data Mining Techniques Used in CRM
4.2 Analysis of Customer Data
4.3 Prediction and Personalization in CRM
4.4 Evaluation of Data Mining Results
4.5 Recommendations for Implementation

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Conclusion
5.3 Implications for Practice
5.4 Recommendations for Future Research

Brief Overview of Thesis:

Data mining techniques have become increasingly popular in the field of customer relationship management (CRM) as organizations seek to better understand and serve their customers. This thesis explores the integration of data mining techniques in CRM and the benefits and challenges associated with this approach.

The study begins with an introduction to the background and significance of the research, outlining the objectives, scope, and limitations of the study. A comprehensive review of relevant literature is conducted in Chapter 2, examining the key concepts of data mining, CRM, and the integration of the two.

Chapter 3 details the research methodology, including the design, data collection methods, analysis techniques, and sampling strategy. The discussion of findings in Chapter 4 presents the results of the data mining analysis, focusing on the techniques used, analysis of customer data, and predictions for personalization in CRM.

The thesis concludes with Chapter 5, summarizing the findings, drawing conclusions, and providing recommendations for practice and future research in the field of data mining techniques for customer relationship management.

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