In this thesis, a framework has been developed to identify the potential of geospatial sales in the agriculture & automotive sector. The models used so far do not take into account the territorial, demographic and economic component, often based solely on the data provided by companies, leading to investments and choices based only on internal data, not taking into account the context and possible competitors. By integrating the company's data with geospatial, economic and statistical data, it was possible to develop an exploratory and subsequently elaborate and predictive pipeline. Following various analyzes of the reference KPIs, we defined and tested different models for predicting earnings and identifying the potential of dealer collections on a provincial basis.