The outlier data mining research is of great significance to ensure the reliable operation of data mining. However, the models adopted in the international marketing mining data research at present make use of only one of the time or spatial correlation mining. Taking the defects of the existing international marketing outlier data mining models and the spatial and temporal correlation of the error matrices into full consideration, a kind of international marketing outlier data mining model that relies on the subdivision market analysis algorithm (hereinafter referred to as SMAA for short) is put forward. In this model, the dimensionality reduction capacity of SMIA and the multi-scale modeling capacity of the subdivision transformation are fully leveraged to construct an international marketing outlier data mining model. In the analysis of the international marketing outlier data, it is mainly achieved through the SMAA. In addition, the sliding window mechanism is effectively used to achieve the online expansion of the international marketing outlier data mining model, and thus the international marketing outlier data mining model dependent on the online subdivision market analysis is obtained. Through the analysis of the international marketing outlier data mining and the simulation results thus obtained, it can be concluded that the international marketing outlier data mining model dependent on the subdivision market analysis has more prominent advantages compared with the BSA model and the detection performance is more superior.