IT Management Strategies for Implementing Personalized Marketing with Machine Learning in the U.S. Retail Sector

Md Azhad Hossain; Arif Hosen; Arifa Ahmed; Fahad Ahmed; MD Ahsan Ullah Imran; Mustakim Bin Aziz; Syeda Kamari Noor; Arif Ahmed  Sizan

doi:10.63332/joph.v3i3.2586

Authors

Md Azhad Hossain Department of Business Administration, International American University, Los Angeles, CA 90010, USA
Arif Hosen Department of Business Administration, Trine University, Angola, IN 46703, USA
Arifa Ahmed Department of Business Administration, International American University, Los Angeles, CA 90010, USA
Fahad Ahmed Department of Science in Engineering Management, Trine University, Angola, IN 46703, USA
MD Ahsan Ullah Imran Department of Business Administration, Westcliff University, Irvine, CA 92614, USA
Mustakim Bin Aziz Department of Business Administration, Westcliff University, Irvine, CA 92614, USA
Syeda Kamari Noor Department of Business Administration, Westcliff University, Irvine, CA 92614, USA
Arif Ahmed Sizan Department of Business Administration, Westcliff University, Irvine, CA 92614, USA

DOI:

https://doi.org/10.63332/joph.v3i3.2586

Keywords:

Retail industry, Marketing strategies, Machine learning, Data-driven insights, Customer

Abstract

In the dynamic landscape of the U.S. retail industry, personalized marketing has become a vital approach to strengthening customer engagement and driving sales. This paper investigates the application of machine learning (ML) techniques to create customized marketing strategies that align with individual consumer preferences and behaviors. By leveraging extensive datasets from both online and in-store transactions, the study utilizes predictive analytics to segment customers, deliver targeted product recommendations, and design personalized promotional campaigns. The integration of ML enables retailers to better understand their customers, leading to more meaningful interactions and improved shopping experiences. The results demonstrate that businesses employing ML-driven personalization report significant improvements in engagement metrics, increased brand loyalty, and higher conversion rates. This research highlights the transformative impact of data-driven insights on retail marketing strategies and offers practical guidance for retail managers seeking to stay competitive by enhancing the customer journey through technology-enabled personalization.