AHFE Open AccessA Data-Driven Method for Cross-Regional User Insight
Abstract
In the context of globalization, products and services are increasingly designed for users from diverse cultural backgrounds. How to generate user insights that are both interpretable and translatable across different social structures, cultural psychologies, and institutional environments has become a central methodological challenge in cross-regional user research. Existing studies often exhibit a disconnection between macro-level national or contextual analysis and micro-level user experience insights: macro analyses are difficult to translate into concrete design decisions, while experience-based data analysis frequently lacks systematic interpretation within institutional and cultural contexts.To address this gap, this paper proposes a data-driven method for cross-regional user insight based on the integration of multi-source data and a layered analytical framework. The proposed method consists of three interrelated layers. At the practical layer, macro statistical data and social event frequency analysis are used to quantitatively examine material environments and survival constraints across regions. At the theoretical layer, natural language processing (NLP) techniques are applied to user-generated content to analyze emotional tendencies and value semantics, revealing culturally embedded psychological perceptions. At the strategic layer, the AEIOU framework is employed to structurally analyze everyday practices and infer broader lifestyle paradigms and institutional influences from the bottom up.Triangulation is introduced as the core analytical strategy to independently encode and cross-validate findings across the three layers, enabling the identification of cross-regionally consistent core needs as well as potential design opportunities exposed by structural differences. The concept of “comfort” is used as an application context to demonstrate the feasibility of the proposed method. The results indicate that this approach enhances both the explanatory depth and application stability of cross-regional user insights, providing methodological support for user research and decision translation in global design practices.
Keywords: Cross-regional User Insight, Big Data User Research, Cross-cultural Research Methods, Sentiment Analysis, Triangulation-based Validation
DOI: 10.54941/ahfe1007343
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