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Introduction

In the rapidly evolving landscape of retail, the concept of omnichannel has gained significant traction in recent years. Omnichannel retail refers to the integration of multiple channels, such as physical stores, online platforms, and mobile apps, to provide a seamless and cohesive shopping experience for customers. With the rise of e-commerce and digital technologies, customers now have more options and touchpoints than ever before when interacting with retailers. This shift has created new challenges and opportunities for businesses to understand and predict customer behavior across various channels.

Predicting customer behavior in omnichannel retail is crucial for businesses to effectively engage with their customers, optimize their marketing strategies, and ultimately drive sales and loyalty. By leveraging data analytics and machine learning techniques, retailers can gain valuable insights into customer preferences, purchase patterns, and decision-making processes. This allows them to personalize their marketing campaigns, tailor their product offerings, and improve the overall customer experience.

This thesis aims to explore the factors influencing customer behavior in omnichannel retail and develop predictive models to forecast customer actions and preferences. By combining theoretical frameworks, empirical research, and advanced analytical methods, this study seeks to provide a comprehensive understanding of customer behavior in the omnichannel environment and offer practical implications for retailers.

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 Evolution of Omnichannel Retail
2.2 Customer Behavior in Omnichannel Retail
2.3 Data Analytics and Predictive Modeling
2.4 Personalization in Retail Marketing
2.5 Customer Segmentation and Targeting
2.6 Technology Adoption in Retail
2.7 Competitor Analysis and Benchmarking
2.8 CRM and Customer Engagement
2.9 Customer Lifetime Value
2.10 Ethics and Privacy Concerns

Chapter 3: Research Methodology
3.1 Research Design
3.2 Data Collection
3.3 Data Analysis Techniques
3.4 Sampling Methods
3.5 Model Development
3.6 Hypothesis Testing
3.7 Variable Selection
3.8 Model Validation

Chapter 4: Discussion of Findings
4.1 Descriptive Analysis
4.2 Inferential Analysis
4.3 Predictive Modeling Results
4.4 Managerial Implications
4.5 Practical Recommendations
4.6 Future Research Directions

Chapter 5: Conclusion
5.1 Summary of Findings
5.2 Contributions to Theory and Practice
5.3 Limitations and Future Research
5.4 Conclusion and Final Remarks

This thesis will provide a comprehensive overview of predicting customer behavior in omnichannel retail, with a focus on the theoretical underpinnings, empirical evidence, and practical implications for businesses. By examining the key drivers of customer behavior, leveraging advanced analytical techniques, and offering actionable insights, this study aims to contribute to the growing body of knowledge on omnichannel retail and enhance the strategic decision-making process for retailers in the digital age.

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