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Introduction

The concept of predicting customer lifetime value (CLV) has gained significant importance in the field of marketing and customer relationship management. With the increasing competition in the market, companies are constantly looking for ways to retain their existing customers and attract new ones. Understanding the value of a customer over their lifetime can help businesses make informed decisions regarding their marketing strategies, customer acquisition, and retention efforts.

This thesis aims to explore the various methods and techniques used in predicting customer lifetime value, with a focus on their application in real-world business scenarios. By analyzing customer data and behavior, businesses can gain insights into the future value of their customers and tailor their marketing efforts accordingly.

Table of Contents

Chapter 1: Introduction
1.1 Introduction
1.2 Background of the Study
1.3 Problem Statement
1.4 Objective of Study
1.5 Limitation of Study
1.6 Scope of Study
1.7 Significance of Study
1.8 Structure of the Thesis
1.9 Definition of Terms

Chapter 2: Literature Review
2.1 Overview of Customer Lifetime Value
2.2 Theoretical Framework of CLV
2.3 Methods of Predicting CLV
2.4 Factors Influencing CLV
2.5 Importance of CLV in Marketing
2.6 Challenges in Predicting CLV
2.7 Applications of CLV in Business
2.8 Comparison of CLV Models
2.9 Case Studies on Predicting CLV
2.10 Summary of Literature Review

Chapter 3: Research Methodology
3.1 Research Design
3.2 Data Collection Methods
3.3 Sampling Techniques
3.4 Data Analysis Techniques
3.5 Model Development
3.6 Validation of Models
3.7 Ethical Considerations
3.8 Limitations of the Study
3.9 Research Timeline

Chapter 4: Discussion of Findings
4.1 Analysis of Data
4.2 Comparison of Models
4.3 Insights into Customer Behavior
4.4 Implications for Business Strategies
4.5 Recommendations for Future Research
4.6 Limitations of the Study
4.7 Managerial Implications
4.8 Conclusion of Results

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Conclusion
5.3 Recommendations for Practice
5.4 Recommendations for Future Research
5.5 Contributions to Knowledge
5.6 Conclusion

Thesis Overview

The prediction of customer lifetime value (CLV) is a crucial aspect of marketing strategy that can help businesses enhance their customer relationship management and maximize their profitability. This thesis aims to provide a comprehensive overview of the methods and techniques used in predicting CLV, with a focus on their practical applications in real-world business scenarios.

Chapter 1 introduces the topic of predicting customer lifetime value, providing a background of the study, problem statement, objectives, limitations, scope, significance, structure of the thesis, and definition of terms. Chapter 2 presents a detailed literature review on CLV, including its theoretical framework, methods of prediction, factors influencing CLV, importance in marketing, challenges, applications, models comparison, and case studies.

Chapter 3 outlines the research methodology, including research design, data collection and analysis methods, sampling techniques, model development, validation, ethical considerations, limitations, and research timeline. Chapter 4 discusses the findings of the study, analyzing data, comparing models, providing insights into customer behavior, implications for business strategies, recommendations for future research, and managerial implications.

Chapter 5 concludes the thesis, summarizing the findings, conclusions, recommendations for practice and future research, contributions to knowledge, and final thoughts on predicting customer lifetime value. Overall, this thesis aims to contribute to the existing literature on CLV prediction and provide valuable insights for businesses looking to enhance their customer management strategies.

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