Power Marketing Big Data Precision User Profile

Abstract

Aiming at the new market competition environment, grid companies are shifting from traditional passive and extensive management services to active and innovative marketing services, a power marketing user profile model method is proposed, which is based on the classic RFM user value model, analyzes the relevant characteristics that affect the user value of power payment, and extracts the five characteristics of C, R, F, M and O to construct the CRFMO power payment user value model. Secondly, the K-Means clustering algorithm is used to group users to realize user profile. The experimental results show that the model method lays the foundation for the power company to effectively mine user power payment information, extract user value, and formulate corresponding marketing strategies and provide differentiated services.