Algorithmic Personalization in Social Media Marketing: Shaping Public Perception and Driving Consumer Behavior

This study investigates the impact of algorithmic personalization in social media marketing, specifically focusing on how it shapes public perception and influences consumer behavior. Through qualitative content and discourse analysis, the research explores how algorithmically tailored messages are designed to align with users’ interests and emotions and drive brand awareness, customer loyalty, and engagement. The theoretical framework is based on consumer behavior models and strategic communication theories, aiming to identify key trends in content distribution that optimize marketing outcomes. The findings reveal that algorithmic personalization is a tool for enhancing user experience and a powerful means of fostering emotional connections with brands and constructing narratives that resonate with audience values. However, the analysis also uncovers challenges, including the risks of consumer manipulation and the restriction of exposure to diverse perspectives, which pose significant ethical concerns. In conclusion, while algorithmic personalization has the potential to revolutionize digital marketing, it requires careful implementation to balance business objectives with ethical content management. Practical implications include recommendations for developing transparent, inclusive, and adaptive marketing strategies that cater to the increasingly sophisticated expectations of digital audiences.