Personalized Marketing Strategy in Digital Business Using Data Mining Approach

Abstract

The integration of personalized marketing strategies and data mining techniques in the realm of digital business has garnered significant attention in recent years. This study employs a mixed-methods approach to explore the dynamics between personalized marketing and data mining, specifically investigating customer perceptions and behavior in the Lhokseumawe and Cirebon regions. Through in-depth interviews, 80 respondents' views on personalized marketing were analyzed, highlighting both positive sentiments regarding tailored campaigns and concerns over data privacy. Furthermore, quantitative analysis was conducted using data from platforms such as WhatsApp, Instagram, TikTok, and Shopee Ecommerce. This revealed distinct customer segments, yielded improved product recommendations, and uncovered interesting purchasing patterns. The results emphasize the importance of striking a balance between personalization benefits and privacy protection. By harnessing the insights provided by data mining, businesses can enhance customer engagement and satisfaction, ultimately navigating the dynamic digital landscape more effectively. This study contributes practical implications and strategic insights for businesses seeking to optimize their digital marketing strategies.