International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Leveraging Artificial Intelligence for Context-aware Marketing in Mobile Commerce Applications

Author(s) Sushant Ubale
Country United States
Abstract This article explores the integration of artificial intelligence in contextual marketing within mobile commerce applications, focusing on the development and implementation of sophisticated AI-driven systems for enhanced user experiences. The article investigates how AI algorithms can effectively analyze user behaviors, purchasing patterns, and real-time contextual data to deliver personalized marketing experiences in mobile commerce platforms. It examines the technical foundations of AI-driven marketing systems, including machine learning algorithms, deep learning models, and natural language processing capabilities, while addressing the critical aspects of data collection and privacy preservation. The article further delves into the implementation frameworks, system architectures, and performance metrics that enable successful deployment of these systems. Through comprehensive article analysis of behavioral patterns, predictive modeling, and real-time decision systems, this article demonstrates the transformative potential of AI in mobile commerce marketing. The article also addresses technical challenges, privacy considerations, and future directions, providing valuable insights for organizations seeking to leverage AI technologies for improved customer engagement and business outcomes in the mobile commerce landscape.
Keywords Keywords: Artificial Intelligence, Contextual Marketing, Mobile Commerce, Machine Learning, Personalization
Field Computer
Published In Volume 6, Issue 6, November-December 2024
Published On 2024-12-15
Cite This Leveraging Artificial Intelligence for Context-aware Marketing in Mobile Commerce Applications - Sushant Ubale - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.33004
DOI https://doi.org/10.36948/ijfmr.2024.v06i06.33004
Short DOI https://doi.org/g8wkkt
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