Energy managers responsible for large real-estate portfolios typically review Energy Star scores and Energy Use Intensity (EUI) to determine which facilities to target for retrofit or audit. In the case of a large portfolio of small retail facilities, the cost for a full audit can be expensive and the benefits may only be realized when retrofits can be performed across many facilities. This thesis proposes an approach that utilizes a combination of smart meter data and building automation system (BAS) data. The authors have tested this approach across two retail bank portfolios consisting of approximately 2,000 locations. The proposed approach uses a combination of change-point models coupled with in-person audits and BAS time series data analysis to extract key features driving energy use. The thesis includes results from a field study demonstrating the impact of the retrofit measures proposed by the developed system.