Research on user profiling based on Apriori algorithm for power marketing big data

The types of electricity users are increasing, electricity consumption is growing significantly, and user demands for power services are becoming more diverse. By leveraging big data technology to deepen the analysis of customer behavior characteristics, a precise customer profiling strategy has been developed, resulting in a user-centric profiling system. This system labels user data to abstract key features such as individual attributes, consumption preferences, and behavioral habits, providing a comprehensive depiction of user information. The study first utilizes a Black Friday shopping platform dataset to extract static and dynamic data, which are then used to generate three types of labels: statistical labels, rule-based labels, and mining-based labels. These labels correspond to the individual attribute module, individual consumption capability module, and product preference module, respectively, offering precise user services and personalized recommendations in the field of electricity marketing.