Abstract. In order to find out the relationship between the price sensitivity and actual market acceptance degree of metallic materials, the database ensemble learning model is proposed in this paper. Due to the variety and class imbalance of customers, a database marketing model based on supervised clustering and ensemble learning is used for the model. The results show that the database ensemble learning model can thus improve the calculation accuracy and time-efficiency substantially.