Who’s a Good Fit for Electrification? Data-Driven Customer Analysis
Before rolling out an electrification program you need to know who, within your customer base, is the most likely to benefit from electrification. This usually means moving people from delivered fuel (oil or propane) to electric or updating an older electric system. While a utility or other organization may have a lot of information about their customers and utilities may have access to energy usage data, it is unlikely that they have a complete picture of all of their customers. For this presentation, we’ll show how Eversource was able to enhance standard customer information with likely heating fuel values to segment audiences based on their interest in or benefits from potential electrification strategies.
Using customer address, usage, previous participation data, data shared between utilities, tax assessors data, Experian data and gis data, we classified customers as heating with electricity, natural gas, delivered fuels, fossil fuels (gas or delivered but unknown which) or unknown. Prior to the analysis, 84% of heating fuels were unknown. After imputation, unknowns dropped to 14%. In this presentation we walk through this process of customer identification and offer examples of how we’re seeing these datasets inform other marketing campaigns and implementation strategies to bolster our customer’s adoption of electrification solutions.
Meghan O’Connor is a Senior Analyst in Energy Efficiency with Eversource. She works with program administrators to understand who their customers are and what factors motivate participation in EE programs. After 15 years in environmental consulting Meghan brought her analytics skills to energy efficiency. Meghan holds a M.S. in Biology from Northeastern University.