From Data to Loyalty : A quantative study of consumer's response to AI-driven personalized marketing

Background: The increasing reliance on Artificial Intelligence (AI) in personalized marketing has reshaped consumer interactions in the digital era. With technological advancements, there is a growing need to explore how AI-driven personalization influences consumer behavior, particularly in satisfaction, loyalty, and ethical considerations. Purpose: This thesis investigates the impact of AI-driven personalized marketing on consumer perceptions, attitudes, and behaviors. It aims to understand how trust and ethical considerations such as data privacy and algorithmic bias influence consumer responses and engagement with personalized marketing. Method: Employing a quantitative approach, this study integrates quantitative analysis from surveys conducted on 100 participants. This method provides a comprehensive understanding of the implications of AI-driven personalization. Statistical tools like SPSS were used for data analysis, ensuring rigorous examination of the collected data. Conclusion: The findings reveal a nuanced response to personalized marketing. While AI-driven personalization can enhance consumer engagement and satisfaction, transparency and ethical considerations are critical in securing consumer trust and loyalty. The study underscores the importance of ethical marketing practices and the need for continuous adaptation to technological advancements to align with consumer expectations and ethical standards. This research contributes to academic discussions on personalized marketing and offers strategic insights for integrating technological advancements with consumer-centric approaches in marketing practices.