Beyond Random Sampling: Behavioral Targeting As a Human Factors Methodology For Uncovering Latent Citizen Needs In Government Web Services

Abstract

Government digital services are built on an implicit promise of universal accessibility, yet the methods most commonly used to evaluate them are structurally incapable of capturing the experiences of those who depend on them most. This paper examines a persistent methodological gap in public sector UX evaluation: the reliance on random sampling, which systematically dilutes the feedback of task-motivated citizens with the opinions of users who have never encountered the service's core failure points. Drawing on a case study of a municipal web portal redesign in Japan, we present a behavioral targeting approach in which a real-time analytics platform identifies purposeful visitors — defined operationally by scroll depth — and delivers satisfaction surveys exclusively to this segment. This method is grounded in the principle of ecological validity: measuring users within the context of genuine task performance rather than through decontextualized recall. The targeted survey revealed an overall Net Promoter Score (NPS) of -52.3, a navigation failure rate of approximately 25%, and three prioritized failure dimensions identified through journey map analysis. A subsequent redesign, anchored in smartphone-first architecture and AI-assisted search functionality, produced measurable improvements validated by post-launch citizen feedback. From these findings, we propose a replicable Behavioral Targeting Evaluation Model (BTEM) for public sector usability assessment. The implications extend well beyond the Japanese context: as local governments worldwide accelerate digital transformation, the ability to isolate and address the right users' failures — rather than averaging across the full population — will determine whether digital public services achieve genuine public value.

Keywords: Government UX, Behavioral Analytics, Citizen Experience, Human-centered Design, Public Sector Digital Transformation, Net Promoter Score

DOI: 10.54941/ahfe1008043