Dr Manpreet Kaur 01 01 Social media algorithms have become a significant determinant of brand performance and customer engagement in the contemporary digital marketing environment These algorithms driven by machine learning technologies and analyses of user behavior prioritize content based on factors such as relevance engagement levels viewing history and interaction patterns As a result they influence the content that users encounter on their social media feeds This study examines the role of social media algorithms in shaping brand visibility and their subsequent impact on customer engagement metrics including likes shares comments clickthrough rates and conversion behavior Adopting a conceptual and analytical approach the research explores how algorithmic filtering affects both organic reach and paid promotional campaigns across major social media platforms such as Instagram Facebook YouTube and TikTok The study further investigates the implications of these algorithms for content marketing strategies influencer collaborations and customer relationship management practices The findings indicate that algorithmdriven visibility plays a crucial role in determining a brands online success To maintain relevance and engagement brands must adopt diversified content strategies that emphasize personalization interactivity and valuedriven communication However the study also identifies several challenges associated with algorithmic systems including declining organic reach potential algorithmic biases and dependence on platformspecific mechanisms which may disproportionately affect smaller businesses While social media algorithms enhance user experience by delivering more relevant content they simultaneously require brands to continuously adapt their marketing strategies to sustain visibility and foster meaningful customer engagement in an increasingly competitive digital landscape Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026