Multi-dimensional B2B User Persona: Results from a Systematic Review of Research Methods

Abstract

In enterprise-level (B2B) services, due to the wide range of requirements, lengthy decision-making processes, and notable variations in usage circumstances, user research is more complicated compared to C2C services. Especially in the field of cloud computing, how to balance online behavioral data, emotional expressions, and business demands has become the core challenge of user research. Traditional single-point surveys are unable to meet this requirement and call for more systematic and multi-dimensional methodological support. This study, through the collection of 153 questionnaires and 7 targeted customer interviews, proposes brand-new multi-dimensional B2B user persona research methods. The core lies in the integration of mixed research methods and dynamic profiling modelling. The former combines qualitative research (deep/telephone interviews) with quantitative research (NPS, online behavior analysis) and introduces real-time session analysis technology to improve the breadth and accuracy of insights; the latter departs from the static tagging model and dynamically generates visual decision heat maps based on behavioral data, graphically presenting the concerns, influence, and information sources of different roles. These methods can compensate for the limitations of current research methods by more correctly capturing the dynamic characteristics of enterprise clients. Through multi-dimensional data integration and dynamic persona methodology, the research findings not only provide scientific support for product design optimization, market and sales strategy formulation but also offer a replicable innovative path for B2B user research.

Keywords: B2B, Human-centered, Cloud Computing, User Persona

DOI: 10.54941/ahfe1006865