Building a hyper-personalized maturity model: A strategic path for businesses in the data ERA - Thuy, Nguyen Van; Hai, Chu Thi Hong (Edelweiss Applied Science and Technology, 2025)
In the era of big data and artificial intelligence, businesses face increasing demands for personalized customer experiences. This study introduces the Hyper-Personalization Maturity Model (HPMM), a strategic framework designed to assess and enhance an organization’s personalization capabilities. The model is structured around three foundational pillars—data, technology, and business strategy—collectively supporting the evolution of hyper-personalization efforts. It delineates five progressive maturity levels: Basic, Standardized, Integrated, Automated, and Optimized, each characterized by specific criteria that guide businesses in evaluating their current status and identifying areas for improvement. The development of HPMM followed a mixed-methods approach, integrating insights from a comprehensive literature review and expert interviews. An empirical assessment was conducted on 50 businesses operating in Vietnam’s trade and service sectors to validate the model. The findings reveal that 50% of the surveyed businesses remain at the Basic level, relying primarily on demographic data to deliver uniform customer experiences. In contrast, higher maturity-level businesses leverage multi-channel data integration and AI-driven decision-making to achieve more sophisticated personalization. The study underscores the critical role of data-driven strategies and advanced technologies in enhancing customer engagement and competitive advantage.