A growing number of online-native retailers aim to expand into physical stores, seeking a balance between online and offline engagement. To achieve this, they must analyze their sales data using geospatial analytics to identify the most profitable locations for brick-and-mortar expansion. By clustering data around retail zones in cities like New York and San Francisco, retailers can pinpoint areas with high demand for their products. The analysis also involves assigning predicted values to each cluster based on online sales data and creating models to estimate future sales in new markets. This Location Intelligent approach enables retailers to make informed decisions about site planning, mitigate risks, and increase the chances of success in their brick-and-mortar expansion efforts.