Precision Marketing Strategy Optimization of Cross-border E-commerce Platform Based on Big Data Analysis Technology

With the acceleration of global economic integration and the rapid development of internet technology, cross-border e-commerce platforms have broken the time and space restrictions of traditional trade, and can provide more abundant goods and services for consumers around the world, and also provide a broader market space for businesses. However, in the face of increasingly fierce market competition and personalized consumer demand, the traditional marketing methods used by cross-border e-commerce platforms have obvious disadvantages in practicality and efficiency, which limits the sustainable development of the platform. In this regard, this paper will analyze and deeply explore the application feasibility of big data analysis technology in this field, and propose a brand-new user portrait construction framework to provide necessary data support for the formulation and implementation of precision marketing strategies for cross-border e-commerce platforms. Practice has proved that in Hadoop cluster, Kafka framework is used to integrate multi-dimensional and multi-channel data information of users, and Spark engine is used to complete the corresponding model training and mining processing, so as to obtain a comprehensive and three-dimensional portrait of users, help cross-border e-commerce platforms achieve accurate marketing, and improve marketing effect and user experience.