Availability of fine granularity electricity consumption data is critical for building energy management and designing efficient electric retrofits. Methods have been developed for producing year-long hourly electric load profiles of residential and commercial buildings without the need of direct smart meter measurements, which may incur privacy, data inaccuracy, and security concerns. Many of these techniques are built upon monthly utility bills, some leveraging multiple time-of-use intervals. This work proposed an adaptive building electric load profiling technique, which improves upon the limitations of existing work by introducing a transition period that is not always included in the utility bills, while also considering the impacts of seasonal weather changes. The proposed profiling method is tested on a gas-heated building and a fully electric building. Results show the gas-heated building exhibits better profiling errors compared to the fully electric building, whose electric load is more sensitive to environmental temperature changes, resulting in error outside of the acceptable error threshold during shoulder seasons. However, this may be acceptable as shoulder seasons do not meaningfully impact electric retrofits.