A Review of Data Analytics and Machine Learning for Personalization in Tech Sector Marketing

Authors

DOI:

https://doi.org/10.31181/jscda31202562

Keywords:

Data analytics, Personalization, Digital marketing, Marketing campaign, Machine learning

Abstract

This paper reviews the data analytics and machine learning applications in enhancing the personalization of digital marketing communications within the technology sector. Our review focuses on key areas such as customer segmentation, predictive analytics applications, real-time data processing, and behavioral and sentiment analysis. Using an exploratory and qualitative research approach, we examine 61 articles, reports, and case studies. Our study highlights how data-driven and machine learning methodologies improve customer responsiveness and marketing strategies. Our findings reveal that analytical techniques contribute to increased sales through more personalized advertising, fostering stronger customer relationships. Additionally, the growing adoption of these approaches to strengthen digital marketing is a key trend explored in this secondary data-based research.

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Published

2025-05-11

Issue

Vol. 3 No. 1 (2025): Journal of Soft Computing and Decision Analytics

Section

Articles

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Copyright (c) 2025 Zahra Zare, Annur Islam Sifat, Mumtaz Karatas (Author)

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Zare, Z., Islam Sifat, A. ., & Karatas, M. (2025). A Review of Data Analytics and Machine Learning for Personalization in Tech Sector Marketing. Journal of Soft Computing and Decision Analytics, 3(1), 92-111. https://doi.org/10.31181/jscda31202562