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The importance of demographic segmentation to demand side management programs

As energy efficiency programs mature, implementation contractors and utilities must engage a wide variety of customers with historically low participation in demand side management (DSM) programs, and tailor program offers accordingly. This requires us to think beyond common industry questions such as, “What’s beyond lighting?” or “What’s beyond the low-hanging fruit?” for energy efficiency savings.

In certain segments, there may be some low-hanging fruit that has yet to be picked, hidden behind barriers to program delivery and participation. Simply put, utilities and DSM implementation contractors need to speak the language and understand the needs of specific groups in order to increase awareness of energy efficiency opportunities and achieve program savings.

Slicing the program segmentation pie
For residential DSM programs, enhancing program delivery can begin in the design phase with an in-depth understanding of the utility’s customer base, including what are often collectively referred to as the “hard-to-reach” segments: multi-family, mobile, low-income, non-English speaking, rural, and renter households. These groups have historically low participation in DSM incentive programs due to a variety of market barriers that include household purchasing power, owner-renter arrangements, and even cultural differences in how energy is conceived and consumed.

A recent study on technology diffusion and consumer purchasing habits in Energy Economics found that a certain suite of household characteristics – Hispanic ethnicity, non-English speaking, low income, and renter status—are associated with a decrease in propensity to purchase ENERGY STAR® appliances. According to the authors, “Eliminating these gaps in ENERGY STAR appliance adoption would result in house electricity cost savings of $164 million per year and associated carbon emission reductions of about 1.1 million metric tons per year.”

Highly detailed demographic segmentation is already commonplace for many utilities, planning bodies, and consulting firms. California, for example, has been a leader in producing energy-focused demographic segmentation reporting for investor-owned utilities as well as the California Energy Commission. These reports often employ lifestyle market segmentation tools, such as Nielsen’s Claritas PRIZM®, P$YCLE®, and ConneXions®, which use basic demographic variables to enumerate detailed lifestyle reports. You’ve probably seen these PRIZM segments in various media: The Cosmopolitans, Kids & Cul-de-Sacs, Urban Achievers, and Family Thrifts.

Along with available utility customer data and Census Bureau statistics, these lifestyle segmentation reports help DSM program designers produce program strategies that reflect a thorough comprehension of the needs and networks of specific sub-groups of a utility’s customer population. Renters, for example, can be broken down into subgroups like urban middle-income singles and ethnic blue-collar (see “TecMarket Works 2001,” available on the CALMAC website). These segmentation analyses fuel the design and implementation of DSM programs, from culturally specific customer engagement strategies (e.g., Spanish-language marketing campaign to multi-family households) to enhanced technical support for the execution of energy-saving projects (e.g., direct customer assistance in a customer’s native language).

Analyzing household behavior and demographics
One of the overarching goals of DSM programs is a verifiable and enduring behavioral change in the way households and individuals consume energy. Though largely focused on the adoption of appliances and other end-use devices, lasting energy efficiency savings are also predicated upon energy consumption behavior. Understanding how and why different groups consume energy, however, is a complex multivariate question.

From a statistical or econometric standpoint, the modeling of household energy use is fraught with issues of “multicollinearity,” where observed variables such as income, energy use, household age, and climate geography are correlated with one another. Analyzing the complex equation of “What drives household energy use in what segments?” to identify savings opportunities requires an array of data sources and an integration of methodological approaches at the various stages of program design, measurement, and verification. Such a comprehensive style is necessary from a regulatory standpoint, as behavioral programs are often confronted with challenges in documenting savings as well as concerns around the “rebound effect,” where energy efficiency gains may be offset by behavior that results in a net increase in actual energy consumed.

As part of my ongoing industry work, I have been working as a researcher at the Center for Urban Studies (Portland State University) on a “deep dive” residential behavior research project on behalf of the California Energy Commission (CEC). Funded by the CEC’s Public Interest Energy Research (PIER) Program, the Advanced Energy Behavior Analysis project contributes to the development of next-generation household energy models, data streams, technology, and policy analyses to provide an understanding of residential demand for natural gas, an ascendant source fuel for residential buildings that is consumed both directly and through electricity demands. The project team investigated the latest in econometric and statistical approaches to analyzing household energy consumption behavior; the evolution of Title-24 building efficiency codes; and how energy users within households are addressed and evaluated in policy and program implementation circles.

As the subject matter expert on ethnic demographic and energy consumption, I investigated the history of demographic segmentation in energy programs and reviewed a broad collection of literature on lifestyle and cultural consumption from business, economics, and psychology. In future blogs, I will share insights and best practices from this research into demographic segmentation and behavioral programs for residential energy savings. Please contact me if you have any ideas for potential collaboration or cross-pollination.

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