人工智能在跨境电商客户开发与维护中的应用实践研究

Research on the Application Practice of Artificial Intelligence in Customer Development and Maintenance in Cross-Border E-Commerce

摘要: 为响应全球数字化转型趋势，B2B跨境电商已成为中国外贸增长核心引擎。但出口企业普遍面临客户开发效率低、维护成本高、服务响应慢等挑战，传统客户管理模式难以适配市场需求。本研究聚焦中国出口型B2B跨境电商企业，重点探究预测模型与数据分析两类核心AI技术在客户开发与维护中的应用实践。研究表明，AI预测模型可有效支撑购买行为预测与流失预警，数据分析技术则在市场洞察、客户画像构建、供应链风险预警等场景发挥关键作用，助力精准营销与个性化服务落地。当前中国跨境电商AI应用已逐步普及，未来将向多模态交互、全链路自动化演进，成为跨境电商核心生产力，为行业智能化升级提供重要支撑。

Abstract: In response to the global trend of digital transformation, B2B cross-border e-commerce has become the core engine for China’s foreign trade growth. However, export enterprises generally face challenges such as low customer development efficiency, high maintenance costs, and slow service response. The traditional customer management model is difficult to meet market demands. This study focuses on Chinese export-oriented B2B cross-border e-commerce enterprises, with an emphasis on exploring the application practices of two core AI technologies, namely predictive models and data analysis, in customer development and maintenance. Research shows that AI prediction models can effectively support purchase behavior prediction and churn warning, while data analysis technology plays a key role in scenarios such as market insight, customer profile construction, and supply chain risk warning, facilitating the implementation of precise marketing and personalized services. At present, the application of AI in China’s cross-border e-commerce has gradually become widespread. In the future, it will evolve towards multi-modal interaction and full-chain automation, becoming the core productive force of cross-border e-commerce and providing important support for the intelligent upgrade of the industry.