Thesis Abstract

Abstract
The integration of artificial intelligence (AI) technologies in various industries has revolutionized business operations, including customer relationship management (CRM) in the retail sector. This thesis aims to analyze the impact of AI on CRM in the retail industry, focusing on how AI applications such as chatbots, predictive analytics, and personalized recommendations enhance customer interactions and drive business performance. The research investigates the opportunities and challenges associated with AI adoption in CRM, considering factors such as data privacy, customer trust, and organizational readiness. The study begins with an introduction to the research topic, providing background information on the growing importance of AI in retail CRM. It identifies the problem statement regarding the need to understand how AI influences customer relationships and business outcomes. The objectives of the study include exploring the benefits of AI in CRM, identifying key challenges, and proposing strategies for effective implementation. Limitations of the study, such as data availability and time constraints, are acknowledged, along with the scope of the research, focusing on retail firms utilizing AI for CRM. The significance of the study lies in its contribution to the existing literature on AI and CRM, offering insights for retail managers, marketers, and IT professionals seeking to leverage AI technologies effectively. The structure of the thesis is outlined, detailing the organization of chapters and key research components. Definitions of key terms related to AI, CRM, and retail industry concepts are provided to establish a common understanding of the research context. The literature review explores ten key themes related to AI applications in CRM, including customer segmentation, personalized marketing, sentiment analysis, and omni-channel communication. Drawing on academic research, industry reports, and case studies, this section provides a comprehensive overview of the current state of AI in retail CRM, highlighting best practices and emerging trends. The research methodology section outlines the approach taken to investigate the impact of AI on CRM in the retail industry. Research design, data collection methods, sampling techniques, and data analysis procedures are discussed in detail to ensure the validity and reliability of the study findings. The study employs a mixed-methods approach, combining quantitative surveys with qualitative interviews to gather insights from both customers and retail professionals. Chapter four presents a detailed discussion of the research findings, analyzing the effects of AI on customer relationships, sales performance, and customer satisfaction in retail CRM. The results highlight the benefits of AI-driven personalization, automation, and data analytics in improving operational efficiency and customer engagement. Challenges such as algorithm bias, data security, and ethical concerns are also addressed, underscoring the importance of responsible AI implementation in CRM practices. In conclusion, the study summarizes the key findings and implications for retail managers looking to enhance their CRM strategies through AI integration. Recommendations for future research and practical implications for retail organizations are provided, emphasizing the need for continuous innovation and adaptation in the dynamic landscape of AI-driven customer relationship management. The thesis contributes to advancing knowledge in the field of AI and CRM, offering valuable insights for academia and industry practitioners alike.

Thesis Overview

The project titled "Analyzing the Impact of Artificial Intelligence on Customer Relationship Management in the Retail Industry" aims to investigate the implications of integrating artificial intelligence (AI) technologies into customer relationship management (CRM) practices within the retail sector. This research seeks to explore how AI tools and systems are transforming the way retailers interact with customers, manage relationships, and enhance overall business performance. By analyzing this impact, the study aims to provide valuable insights into the challenges, opportunities, and best practices associated with the adoption of AI in CRM within the retail industry. The research will commence with an introduction that sets the context for the study, followed by a detailed background analysis that highlights the evolution of AI technologies and their increasing relevance in customer relationship management. The problem statement will identify the gaps and issues that necessitate this research, emphasizing the need to understand the specific effects of AI on CRM in retail settings. The objectives of the study will be clearly outlined to guide the research process, focusing on investigating how AI is changing customer interactions, personalization strategies, data analytics, and overall customer satisfaction levels in the retail industry. The limitations of the study will also be acknowledged, recognizing the constraints and boundaries that may impact the generalizability of the findings. The scope of the research will be defined to specify the boundaries within which the study will be conducted, ensuring a focused and coherent analysis of the impact of AI on CRM in retail. The significance of the study will be emphasized to underscore its potential contributions to both academic knowledge and practical implications for retail businesses looking to leverage AI in their customer management strategies. The structure of the thesis will be outlined to provide a roadmap of the research framework, including the chapters, sub-sections, and methodologies that will be employed to achieve the research objectives. Additionally, a comprehensive definition of key terms and concepts will be provided to clarify the terminology and ensure a common understanding of the research context. The literature review will delve into existing research, theories, and empirical studies on AI, CRM, and their intersection in the retail industry. This section will synthesize relevant literature to establish a theoretical foundation and identify gaps that the current study aims to address. The research methodology will detail the approach, research design, data collection methods, sampling techniques, and data analysis procedures that will be employed to gather and interpret data on the impact of AI on CRM in retail. This chapter will provide a clear rationale for the chosen methodologies and ensure the validity and reliability of the research findings. The discussion of findings will present and analyze the research results, drawing insights from the data collected to interpret the impact of AI on various aspects of customer relationship management in the retail sector. This chapter will critically evaluate the implications of the findings, compare them with existing literature, and offer recommendations for practitioners and future research directions. In the conclusion and summary chapter, the key findings, implications, and contributions of the study will be summarized, highlighting the significance of the research and its potential implications for retail businesses. The conclusion will also reflect on the research objectives, limitations, and suggest areas for further exploration in the field of AI-driven CRM in the retail industry. Overall, this research overview sets the stage for a comprehensive investigation into the impact of artificial intelligence on customer relationship management in the retail industry, aiming to advance understanding, provide practical insights, and contribute to the evolving landscape of AI technologies in retail business operations.