Volume 18 No 8 (2020)
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ENHANCING TARGETED MARKETING THROUGH MACHINE LEARNING: LEVERAGING SOCIAL MEDIA INTERACTION FOR PERSONALIZED ENGAGEMENT
Dr.M.P.Revathi, Dr.R.Ravi, J.S.Jaslin, S.Jagatheeswaran
Abstract
This article provides an introductory overview of the utilization of machine learning in targeted marketing based on social media interaction. As social media platforms have become integral to consumers' lives, businesses are increasingly leveraging machine learning algorithms to enhance their marketing strategies. This approach enables personalized and precise targeting, improved customer segmentation, and real-time adaptability. Machine learning algorithms analyze vast amounts of social media data to extract valuable insights on customer preferences, behaviors, and trends. By leveraging these insights, businesses can deliver highly personalized marketing experiences that resonate with individual customers, leading to increased engagement and higher conversion rates. However, challenges such as data quality, privacy concerns, model interpretability, and bias mitigation must be addressed to ensure responsible and effective implementation. Looking ahead, the future prospects of machine learning in targeted marketing based on social media interaction are promising, with advancements in personalization, real-time marketing, hyper-targeting, and ethical AI practices shaping the future of marketing.
Keywords
machine learning, social media interaction, customer segmentation, real-time adaptability
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