The analysis leverages multiple types of spatial data to analyze and predict CPG (Consumer Packaged Goods) sales performance. The study focuses on the Iowa liquor market, using publicly available data from 2012 to 2019. By analyzing sales variations across different locations within the state, the research aims to identify factors driving consumption and variation patterns. The approach involves building spatial models that incorporate various features, such as population demographics, points of interest, and geographic insights. These models are trained on a dataset of SKUs (stock-keeping units) and are validated using metrics like R-squared and mean absolute error. The results show strong modeling capabilities, with the model performing only slightly worse when including additional features. The analysis also reveals that larger volume products tend to perform better than smaller ones, likely due to commercial dynamics involving wholesalers and businesses. By extrapolating the results to the state of Nebraska, the study provides insights into areas with high sales potential for specific SKUs.