基于大数据驱动的跨境电商服装流行趋势预测机制研究

Research on the prediction mechanism of fashion trend of cross-border e-commerce clothing popularity driven by big data

大数据驱动的跨境电商已成为世界经济增长的新动力。为解决跨境消费者需求差异所导致的服装流行趋势预测不精准性问题,以消费者数据为切入点,通过市场研究与数据挖掘,结构化地厘清跨境市场中的数据来源,在处理与分析、呈现与反馈的预测流程中采用数据量化与数据可视化的处理技术,提出流行趋势预测问题的求解方式,建构跨境电商流行趋势数字化预测机制。该研究不仅可以规避传统预测机制中依靠有限数据与主观判断所导致的片面性决策,而且能为服装设计要素的精细化培育与营销推广的高效发展提供参考。

Cross-border e-commerce driven by big data has become a new driving force for world economic growth.To address the imprecision of clothing fashion trend prediction caused by cross-border consumer demand differences,this study takes consumer data as the entry point,constructs a clear source of data in cross-border market through market research and data mining,and uses data quantification and data visualization processing technology to intervene in the prediction process of processing,analysis,presentation and feedback.This study also proposes a solution to the problem of trend prediction,and constructs a digital prediction mechanism of cross-border e-commerce trend.This study can not only avoid one-sided decision-making caused by limited data and subjective judgment in the traditional prediction mechanism,but also build a solid foundation for the fine cultivation of clothing design elements and the efficient development of marketing promotion.