It is evident that the speed of innovation and digital technologies has made big data the principal means for transforming marketing methods in the e-commerce sector. While precision marketing hinges on targeting prospective customers with tailored content, its efficacy now depends heavily on big data analytics. This paper provides an in-depth analysis of the role of data science in personalized marketing within the e-commerce domain. The research focuses on how e-commerce businesses utilize consumer data from online transactions, social networks, and web activities to optimize marketing processes and enhance customer engagement. This study employs a literature review methodology to investigate the application of big data in market contexts for underpinning strategic decision-making and fostering innovation. Its primary methodologies encompass data mining techniques, machine learning algorithms, and models constructed around customer segmentation frameworks. The data sources comprise large-scale e-commerce platforms, marketing analytics reports, and online behavioral tracking datasets. The findings suggest that by exploring big data and its connection to market demands, this research gain deeper insights into its impact on the modern economy, while also acknowledging the potential technological bottlenecks that may emerge in the future.
Chenwei Zhang (Tue,) studied this question.
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