Application of Artificial Intelligence Algorithms in Precision Marketing with Flow Data Analysis Models

Precision marketing is critical in today's competitive e-commerce landscape. This study explores the integration of big data analytic into precision marketing for e-commerce. It introduces innovative data clustering techniques to improve the grouping of data points, thereby increasing the accuracy and speed of analysis. The research presents cutting-edge precision marketing algorithms that use data analytic to optimize tactics in real time. Specifically, the k-mode clustering pattern, a novel k-means algorithm, is proposed to address symbolic data clustering. It modifies the k-means algorithm with a 0-1 matching distance metric, making it suitable for symbolic data sets. The study highlights the critical role of big data analytic and advanced algorithms in effective precision marketing campaigns in digital commerce. In experiments across 10 independent datasets, precision testing results exceed 98.5%.