In order to quantitatively analyze and qualitatively calculate the uncertainty and ambiguity of group users accurately, in this study, a qualitative similarity algorithm based on cloud model theory is designed to build a portrait model for group users. Firstly, the user is divided by the most widely recognized RFM mode-Recency, Frequency, and Monetary. Secondly, the user's behavior is transformed into the user's cloud model label through the cloud model transformation algorithm. The cloud model label is a quantitative representation of user's behavior. Then, the cloud model clustering algorithm is used to classify different types of customers which are the model of customer portrait. Finally, the model is used to guide commercial marketing activities.