Customer Lifetime Value Prediction for Insurance Industry – Complete Phd and Masters Thesis

[ad_1]

Introduction:

The insurance industry is one of the most competitive sectors in the financial services industry, with companies constantly looking for ways to attract and retain customers. Customer Lifetime Value (CLV) prediction is a vital tool that helps insurance companies understand the value of their customers over their entire relationship with the company. By accurately predicting CLV, insurers can make informed decisions about marketing strategies, customer segmentation, and retention efforts.

This thesis explores the use of predictive analytics techniques to predict CLV in the insurance industry. Specifically, this study aims to develop a model that can accurately predict the CLV of individual customers based on their historical data and behavior. By doing so, insurance companies can optimize their marketing efforts, improve customer satisfaction, and ultimately increase profitability.

Table of Contents:

Chapter 1: Introduction
1.1 Introduction
1.2 Background of 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 Concept of Customer Lifetime Value
2.2 Importance of CLV in the Insurance Industry
2.3 Predictive Analytics in CLV Prediction
2.4 Previous Studies on CLV Prediction in Insurance
2.5 Factors Influencing CLV
2.6 Methods for CLV Prediction
2.7 Challenges in CLV Prediction
2.8 Customer Segmentation and CLV
2.9 CLV and Customer Retention
2.10 CLV and Marketing Strategies

Chapter 3: Research Methodology
3.1 Research Design
3.2 Data Collection
3.3 Data Preprocessing
3.4 Feature Selection
3.5 Model Development
3.6 Model Evaluation
3.7 Performance Metrics
3.8 Ethical Considerations

Chapter 4: Discussion of Findings
4.1 Descriptive Analysis of Data
4.2 Model Performance Evaluation
4.3 Factors Influencing CLV Prediction
4.4 Customer Segmentation Analysis
4.5 Comparison with Previous Studies
4.6 Implications for Insurance Companies
4.7 Recommendations for Future Research

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Conclusion
5.3 Contributions to Knowledge
5.4 Practical Implications
5.5 Limitations of the Study
5.6 Suggestions for Future Research

This thesis will provide valuable insights into the prediction of Customer Lifetime Value in the insurance industry, offering practical recommendations for insurers to improve their business strategies and enhance customer relationships.

[ad_2]


Purchase Detail

Download the complete project materials to this project with Abstract, Chapters 1 – 5, References and Appendix (Questionaire, Charts, etc), Click Here to place an order via whatsapp. Got question or enquiry; Click here to chat us up via Whatsapp.
You can also call 08111770269 or +2348059541956 to place an order or use the whatsapp button below to chat us up.
Bank details are stated below.

Bank: UBA
Account No: 1021412898
Account Name: Starnet Innovations Limited

The Blazingprojects Mobile App



Download and install the Blazingprojects Mobile App from Google Play to enjoy over 50,000 project topics and materials from 73 departments, completely offline (no internet needed) with monthly update to topics, click here to install.

Read Previous

Prevalence and correlates of non-suicidal self-injury in college populations – Complete Phd and Masters Thesis

Read Next

The impact of nurse-led interventions on patient outcomes in nephrology settings – Complete Phd and Masters Thesis

Leave a Reply

Your email address will not be published. Required fields are marked *

Translate »