Research on Data Selection of Cross-Border Retail E-Commerce Enterprises from the Perspective of Consumer Search Behavior-Take AliExpress, a Cross-Border E-Commerce Platform, as an Example

In the digital economy era, under the background of increasingly short-term and fragmented consumer demand, cross-border retail e-commerce has gained tremendous development space. When cross-border retail companies go overseas, facing the complex overseas environments and differentiated product demands, data selection can help companies accurately grasp consumer demand. This article studies consumer search behavior data on AliExpress on the cross-border retail e-commerce platform. Based on the analysis of cross-border retail consumer search behavior and the traffic paths it generates, both two indicators were analyzed by Pearson correlation and linear regression analysis. Based on the quantitative relationship between the data indicators, from the perspective of search behavior, data selection research is conducted. Data selection has the nature of the C2B model, providing consumers with more personalized products to meet consumers' differentiated needs, and changing the weak position of consumers in the traditional single selection method. Enterprises meet consumer needs through data, and provide consumers with precision products and services. Therefore, in the context of the rapid development of the digital economy and the digital empowerment of enterprises to promote the transformation of the industry, the research on data selection of cross-border retail e-commerce companies has certain feasibility and practical value.