Abstract

Over 70 million low and moderate income (LMI) Americans struggle to pay their electricity bills each year. Low-income households suffer a disproportionate energy burden, defined as the percentage of gross household income spent on energy costs. Eversource recognizes the needs of its LMI customers and has a long and successful history of helping low income customers weatherize their homes working with local Community Action Program (CAP) agencies, and wanted to do more. Eversource and Oracle Utilities-Opower partnered to develop a first-of-its-kind analytical approach to characterize communities in need and target the customers who need help. While most experts have relied solely on energy burden as a singular metric to characterize need, the Eversource-Opower team intends to employ a data-driven methodology that will leverage individual energy consumption, available customer demographic data, third party data and innovative, open source data sets. The resultant curated portfolio of metrics move beyond burden to illuminate specific characteristics of target communities and create nuanced programs that are specific to the socio-economic needs of a particular area. Preliminary results indicate that by combining the portfolio of metrics, we can find customers who slip through the cracks when we market based on income or neighborhood alone.

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