The growing availability of electric interval data from smart meters is driving development of consumer-facing analytical software that has the potential to offer automated measurement and verification (M&V) of savings from energy efficiency projects. This capability would present new opportunities to utilities including supporting financial transactions based on measured energy savings, or allowing for a greater variety of program measures. This report provides the results of analytical research on establishing a method for developing a robust energy baseline regression model and evaluation of how the model performed on the electric interval dataset from NEEA’s Residential Building Stock Analysis metering study. The report presents results of a literature review and a high-level review of home energy management system (HEMS) M&V capabilities. The results of the analytical research provide a strong foundation for future efforts toward an automated M&V approach using interval data, while the literature review confirmed the team’s initial belief that utilities have not yet applied M&V approaches for residential applications using interval data. Additionally, the HEMS research uncovered no instances of products performing utility program M&V.