In today's world where dynamics of data are so important, using of Spatial Data Infrastructure (SDI) can provide a platform for spatial data sharing. Replacing SDI with GIS in Geomarketing Creates new chapter on Spatial Information-Based e-marketing. SDI-based Geomarketing fixes the flaws and shortcomings of spatial information layers in GIS-based Geomarketing. In this research, a new model of location-based marketing is presented, which uses spatial data infrastructure for the first time. In this regard, based on the available spatial data, Semnan city is divided into 139 statistical areas or urban areas. By sharing the databases of the related executive agencies in the context of spatial data infrastructure, the main demographic and economic indicators related to bank marketing were selected. Through statistical methods of correlation coefficient and multivariate regression, the effective indicators on the number of bank branches have been calculated. The number of businesses index with a coefficient of 0.598 had the greatest impact on the number of bank branches in each region. Finally, using the mentioned demographic, economic and geographical indicators and using the TOPSIS method, the regions of Semnan city were prioritized in terms of banks' marketing indicators, and region 70 has the first priority. The results of the Multiple Attribute Decision Model are considered as a dependent spatial variable in the SDI-based Geomarketing model.
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