Big data-driven customer hierarchical management is a crucial aspect of modern customer relationship management (CRM) systems. With the increasing volume and variety of customer data available, businesses are turning to data mining and customer classification practices to effectively manage and understand their customer base. This is particularly important for overseas store systems, where businesses must navigate cultural and geographical differences to effectively engage with their customers. Data mining is the process of analyzing large sets of data to identify patterns, trends, and insights that can be used to make informed business decisions. In the context of customer hierarchical management, data mining allows businesses to extract valuable information from customer data, such as purchase history, demographics, and online behavior. This information can then be used to segment customers into different groups based on their characteristics and behaviors. Customer classification is the practice of categorizing customers into different groups based on their value to the business. This can include factors such as purchase frequency, average transaction value, and overall lifetime value. By classifying customers into different tiers, businesses can tailor their marketing and customer service efforts to better meet the needs and expectations of each group. Overseas store systems face unique challenges when it comes to customer hierarchical management. Not only do businesses need to understand the preferences and behaviors of customers from different cultural backgrounds, but they also need to navigate language barriers and logistical challenges. Big data-driven customer hierarchical management can help businesses overcome these challenges by providing a comprehensive understanding of their overseas customer base. By leveraging data mining and customer classification practices, overseas store systems can gain valuable insights into the preferences and behaviors of their international customers. This can help businesses identify new opportunities for growth, improve customer satisfaction, and ultimately drive revenue. For example, by identifying high-value customers in specific regions, businesses can tailor their marketing efforts to better engage with these customers and increase their loyalty. In conclusion, big data-driven customer hierarchical management is essential for overseas store systems looking to effectively manage and understand their customer base. By leveraging data mining and customer classification practices, businesses can gain valuable insights into their international customers and tailor their marketing and customer service efforts to better meet their needs. This can ultimately lead to increased customer satisfaction, loyalty, and revenue for overseas store systems.