Thesis Abstract

Abstract
This thesis explores the impact of artificial intelligence (AI) on customer relationship management (CRM) within the retail industry. The integration of AI technologies in CRM practices has revolutionized how retailers engage with customers, personalize interactions, and enhance overall customer satisfaction. This study aims to investigate the implications of AI adoption in CRM for retail businesses, with a focus on understanding the benefits, challenges, and opportunities associated with this technological advancement. The research begins with an in-depth analysis of the background of the study, providing insights into the evolution of CRM practices in the retail sector and the emergence of AI as a disruptive force in customer engagement strategies. The problem statement highlights the need for retailers to adapt to changing consumer behaviors and preferences by leveraging AI-powered CRM tools to deliver personalized and seamless customer experiences. The objectives of the study include examining the impact of AI on customer segmentation, predictive analytics, chatbots, recommendation engines, and other CRM functions in the retail industry. By identifying these key areas, this research aims to provide valuable insights for retailers looking to enhance their CRM strategies through AI technologies. Limitations of the study are acknowledged, including constraints related to data availability, time constraints, and the rapidly evolving nature of AI technologies in the retail sector. Despite these limitations, the scope of the study encompasses a comprehensive analysis of AI applications in CRM within the retail industry, focusing on both theoretical frameworks and practical implementations. The significance of this study lies in its potential to inform retailers, industry practitioners, and academics about the transformative impact of AI on CRM in the retail sector. By understanding the implications of AI adoption in CRM, businesses can develop more efficient and effective customer engagement strategies that drive growth and competitiveness. The structure of the thesis is outlined, with Chapter 1 providing an introduction to the research topic, background information, problem statement, objectives, limitations, scope, significance, and definition of key terms. Chapter 2 presents a detailed literature review on the impact of AI on CRM in the retail industry, covering topics such as customer segmentation, predictive analytics, chatbots, and recommendation engines. Chapter 3 discusses the research methodology, including the research design, data collection methods, sampling techniques, and data analysis procedures. This chapter also outlines the ethical considerations and limitations of the research process. Chapter 4 presents an elaborate discussion of the findings, analyzing the implications of AI adoption in CRM for retailers and identifying key trends, challenges, and opportunities in the field. The findings are supported by empirical evidence and theoretical frameworks, providing a comprehensive overview of the research outcomes. Finally, Chapter 5 offers a conclusion and summary of the thesis, highlighting the key findings, implications for practice, and recommendations for future research. The conclusion synthesizes the main arguments and insights from the study, emphasizing the importance of AI in shaping the future of CRM in the retail industry. In conclusion, this thesis contributes to the growing body of knowledge on the impact of AI on CRM in the retail industry, providing valuable insights for retailers seeking to leverage AI technologies to enhance customer relationships and drive business growth. By exploring the benefits and challenges of AI adoption in CRM, this research aims to inform strategic decision-making and innovation in the retail sector, ultimately leading to improved customer experiences and sustainable competitive advantage.

Thesis Overview