Occupancy related energy-use behavior has a significant influence on building energy consumption. Variations and uncertainties in occupants' energy behavior provide the main obstacle for researchers to analyze and predict the impact of occupant behavior on building energy consumption since commercial buildings often have such a large number of residents with unique energy-use patterns. However, this paper hypothesized that individual occupants have their own individual energy consumption patterns and will typically follow such patterns consistently over time. Thus, this research studies occupant behavior in an office environment to examine whether commercial building's occupant's energy-use behaviors are consistent over time. In particular, this research focuses on delay intervals between the occupancy entry/departure events and the beginning/end of the occupant's energy-consuming behaviors. Occupants' entry and departure events were detected by passively capturing Wi-Fi packets from occupants' smartphones while plug-load monitoring detected the beginning/end and quantity of energy use. Results from a four-week long period of tracking individual occupants confirm that occupants use a consistent pattern of starting and ending their energy-use behaviors. Based on these results, this research supports a framework of non-intrusive occupant load monitoring (NIOLM) for tracking occupant-specific energy consuming behaviors in commercial buildings. In the NIOLM framework, the process of tracking each occupant leverages existing Wi-Fi networks, and building energy-monitoring data aggregates energy-consumption data for occupants. Thanks to this study's findings, NIOLM provides a new opportunity for current industry and research efforts to track occupants' energy-consuming behaviors at a minimal cost.