Consumers await the revolutionary interface that will allow them to control their energy consumption. Besides maximizing efficiency in the home, these units will allow more
Understanding consumers’ likelihood of engaging in smart energy behaviors.
Electric utilities are coming to terms with the business need to better understand and predict the likelihood that diverse customers will engage in new and different energy management behaviors. This need is driven, in part, by public policy imperatives, regulatory mandates, and market conditions, including the need to augment flagging sales growth with new revenue streams.
But another key factor driving utilities’ need for greater insights into customers’ energy management behaviors is the implementation of smart grid initiatives. Even as utilities build the smart grid physical infrastructure, they seek to better understand customer energy use behaviors and develop strategies to accommodate diverse norms. The long-term objective is to encourage smart energy customer behavior on a wide scale.
Utilities face multiple challenges in enlisting customers as smart grid participants. The goal is to enable customer involvement in optimizing when, where, and how much electricity they consume—and increasingly that they generate or store. Fundamentally, this requires a new definition of the customer role in the energy supply chain, predicated on encouraging smart energy behaviors unfamiliar to many customers.
To support utility strategies for enabling targeted behavior change, J.D. Power and Associates, in collaboration with 16 U.S. electric utilities, executed a nationwide research effort designed to segment electric residential customers according to energy usage behavior patterns. The result yielded six diverse behavioral segments, based upon the types of smart energy activities and degrees of control that diverse customer populations will undertake to manage their energy consumption, costs, and environmental impact. In addition to the behavioral segmentation, the research examined current customer knowledge and language patterns relating to smart grid and smart meters; explored customer preferences for smart energy service plans and pricing plans; and measured the linkages between smart energy programs and customer satisfaction.
Utilities have practiced customer segmentation of different stripes for decades. Where there’s been a concrete business need—a clear return-on-investment proposition—segmentation has proven to be both used and useful. Two such applications are load forecasting and predictive modeling of non-payment risk. Estimating load growth based on energy usage patterns and equipment-saturation data yields mission-critical models that drive resource planning and regulatory imperatives. Multivariate statistical modeling that anticipates customer likelihood to pay—or not pay—has proved to be an effective tool for reducing bad debt expense and mitigating collections related costs.
However, segmentation intended for customer marketing purposes has a mixed track record. This can be partly attributed to the uneasy relationship between regulated utilities and their own marketing functions. More specifically, utility experience has shown that for customer segmentation to achieve measurable success, it needs time and resources to mature as well as hard-earned employee confidence and acceptance—and, most important, a clear business objective that drives the segmentation solution design, not the other way around.
The strategic charter for smart energy consumer behavioral segmentation is clear. The goal is behavior change, and the solution is segmentation predicated on