This paper presents a solution for collecting user action data for the B2B model. Collecting user data plays an important role in personalized experience, product improvement and business strategy optimization. Data helps Internet platforms publish personalized content and products, and helps businesses optimize subsequent campaigns and improve advertising performance. In addition, data also helps improve customer service, detect errors and prioritize user interfaces. In the field of AI and Machine Learning, data is an important foundation for training models, making the system smarter and more automated. By effectively exploiting user data, businesses can make accurate decisions, optimize operating processes and anticipate market trends, thereby improving performance and quality services. Collecting user data not only helps individuals experience and optimize business strategies, but also opens up opportunities for businesses to provide data collection and analysis services in a B2B (Business to Business) model. Many companies do not have the ability to automatically collect and process big data, so they turn to third-party data aggregation services from various sources. These businesses use the data to optimize subsequent campaigns, anticipate consumer trends, and improve products. The approach and results of this discussion can be fully applied to other types of user data.