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

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.