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Using a reference case from the fashion industry, we introduce how to use the static and dynamic information of the customer to build big data models based on machine learning, such as customer value segementation, customer preferences, customer life cycle stages, customer churn prediction, etc., according to the requirements of different customer segments.We then look at how to design a personalized campaign strategy and to leverage marketing automation tools, and ultimately improve customer loyalty, customer order value and customer value of the entire life cycle.
通过一个鞋服行业的案例分享,介绍如何利用客户的静态及动态信息进行基于机器学习的大数据分析,比如客户价值分析、消费偏好分析、客户生命周期阶段、客户流失预测等分析,根据不同客户群体的需求差异,设计针对性维护/促销活动,并结合自动化的营销工具, 从而最终提升客户忠诚度、客单价值以及客户整个生命周期价值。