Abstract
This study examines the impact of social media on consumers’ purchasing behavior using an integrated approach that combines theoretical frameworks, empirical data analysis, and advanced technological solutions. The study utilizes a mixed method approach combining quantitative analysis of user engagement metrics and qualitative assessment of content effectiveness. The main results indicate the significant influence of social proof, information cascades, and the echo chamber effect on consumer decision–making in digital environments. The study proposes a novel multifactor content optimization system (CMOS) that uses machine learning algorithms for semantic analysis, computer vision, virality prediction, and dynamic pricing. The implementation of CMOC can significantly improve marketing effectiveness and consumer engagement. This study contributes to the field by providing a holistic framework for understanding and optimizing social media marketing strategies, highlighting the importance of ethical considerations and creating true value in digital consumer interactions.
Published Version
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