Core Insights - The e-commerce industry is highly competitive, and user behavior analysis serves as a valuable approach for companies to understand user patterns, preferences, and pain points, enabling them to develop targeted strategies [2]. Funnel Analysis Model - Funnel analysis is a method used to analyze conversion and drop-off rates at various stages of user interaction, providing a visual representation of user transitions from browsing to purchasing [3]. - A typical funnel model in e-commerce includes stages such as browsing products, adding items to the cart, submitting orders, and completing payment [4][5][6][7]. - By analyzing conversion and drop-off rates at each stage, companies can identify critical points of user loss and optimize processes to improve conversion rates [7]. Path Analysis Model - Path analysis helps in understanding user behavior by tracking their navigation paths on a website or application, revealing patterns and preferences [13]. - The implementation steps for path analysis include defining path nodes, collecting data on user interactions, analyzing path patterns, and optimizing path design to enhance user experience [14][15][16][17]. User Segmentation Model - User segmentation involves categorizing users based on characteristics such as age, gender, region, and behavior patterns, allowing companies to tailor marketing strategies and product offerings [18]. - The steps for user segmentation include defining segmentation dimensions, collecting relevant data, conducting segmentation analysis, and formulating targeted strategies based on the findings [19][20][21][22][23]. Retention Analysis Model - Retention analysis assesses user retention over time, calculating retention rates at various intervals to gauge user loyalty and activity levels [24]. - The implementation steps for retention analysis involve defining retention time points, collecting user behavior data, calculating retention rates, analyzing retention patterns, and optimizing retention strategies based on insights [25][26][27][28]. Continuous Improvement - Companies need to integrate multiple analysis models and continuously optimize their data analysis processes to better meet user needs and enhance user experience, ultimately achieving sustainable business growth [29].