Abstract
Designing effective and targeted policies to reduce household emissions needs to consider variability in household consumption patterns, preferences, and financial capacities. This paper introduces a new segmentation model of household carbon footprints that uses financial transaction data from over 700,000 customers of a major high‐street bank. Our approach considers socioeconomic, consumer‐preference, and spatial factors to identify 10 distinct household typologies. We focus on targeted retrofit as a practical application, identifying three high‐impact household types with the capacity to invest— “Suburban Home Improvers,” “Car and Tech Enthusiasts,” and “Affluent Families”— and suggest targeted policy and communication opportunities. Our segmentation supports a new data‐driven policy design that considers both the technical potential and diverse behavioral factors affecting decarbonization decisions.