Investigating Challenges and Identifying Prospective AI Applications for the Advancement of Customer Journey in Marketing

Abstract

This thesis is about the integration of artificial intelligence (AI) into the customer journey within B2B marketing. The main objective is to identify potential areas of use, benefits and challenges that come with the use of AI to enhance the customer journey. With the rapid advancement of AI technologies, businesses must use these tools to remain competitive. AI's role in the customer journey, in regard to pre-purchase and post-purchase phases, can significantly enhance various areas in marketing, including personalization, customer support as well as content creation. The motivation behind this research is to understand how AI can be effectively utilized in the customer journey to provide customer experiences and to address the competitive pressures businesses face in the B2B market. The study also acknowledges several limitations, including the rapidly evolving nature of AI technologies and the specific focus on B2B marketing, which may limit the generalizability of the findings. Existing literature primarily focuses on the benefits of AI in managing the customer journey or on specific AI applications. However, there is a notable lack of studies that address the potential drawbacks and challenges of AI integration, particularly in the context of B2B marketing. This research aims to fill this gap by looking both the benefits and the limitations of AI in the customer journey. The study is centered around the following key research questions: 1. What are the advantages and disadvantages of incorporating AI tools at different stages of the customer journey (pre-purchase, purchase, and post-purchase)? 2. How do businesses mitigate the potential negative impacts of AI on the customer journey? 3. What specific challenges do businesses face when integrating AI into the customer journey? 4. How can businesses balance the benefits and drawbacks of AI to ensure a positive overall impact on customer experience? The research is structured into several key sections. The Introduction defines the problem and research gap, setting the stage for the study. Following this, the literature review discusses the evolution and current state of AI applications in marketing. The case study section gives insights through the analysis of a specific business's AI integration process, showing real-world applications and challenges. The research questions define the main questions of the study, focusing the research on key areas of interest. The conclusion and outlook summarize the findings and suggests future research directions as well as managerial recommendations. The findings indicate that AI can significantly optimize customer interactions and marketing processes. However, challenges such as data privacy risks, algorithmic bias, and the need for transparency are significant. Effective AI implementation requires strategic planning, ethical considerations.

Date of Award	2024
Original language	English
Supervisor	Georg Feichtinger (Supervisor)