Our energy system is rapidly transforming, partially due to advances in internet and communications technologies that leverage an unprecedented amount of data. Industry proponents of the so-called "smart grid" suggest these technologies facilitate deeper engagement with end-users of energy (utility customers) that can in turn drive behavior-based changes and accelerate a renewable energy transition. While there has been progress in understanding how these technologies change consumer behavior using, for example, real-time feedback, it's unclear how specific segments (e.g., renters) respond to these interventions; it's also unclear why feedback is, or is not, producing changes in energy consumption. The literature suggests that behavioral strategies (e.g. information feedback, competitions, incentives) coupled with technology may present a way for utilities and efficiency programs to create savings--expanding opportunities for those often underserved by traditional approaches, such as renters--yet this coupling is not well understood, neither broadly (for all end users) nor specifically (for renters). This dissertation builds upon that literature and explores a human side of the smart grid, using a field experiment in renter households to test the interacting effects of real-time energy feedback and a novel form of financial incentive, referred to here as a competitive performance-based incentive. The experiment had two phases: phase one tested the feedback against a control group; phase two tested feedback, the incentive, and a combined treatment, against a control group. Results of these interventions were measured with pre- and post-treatment surveys as well as observed electricity consumption data from each household's smart meter. The results of this experiment are described in three papers. Paper one examines the interventions' individual and combined effectiveness at motivating renters to reduce or shift timing of electricity consumption. Feedback alone produced a significant savings effect in phase one. In phase two, the effect of the feedback wore off; the incentive alone had no significant effect; and the group that received feedback and the incentive experienced a doubling of savings relative to the effect of feedback alone, as observed in phase one. Paper two uses pre- and post-intervention survey data to examine how individual perceptions of energy change as a result of the interventions. Perception of large energy-using appliances changed the most in households that received feedback, suggesting that better information may lead to more effective behavior changes. Paper three leverages the results of the first two components to evaluate the policy implications and impacts on demand side management for utilities, efficiency programs, and the potential for behavior-based energy efficiency programs. Advocates of the smart grid must recognize the technology alone cannot produce savings without better engagement of end-users. Utility rate designers must carefully consider how time-based rates alone may over-burden those without the enabling technology to understand the impact of their energy choices.