Elevating Game User Research with a Guided Interface for Data Analysis

The game user research field faces a persistent challenge in bridging the gap between complex statistical analysis and the practical needs of development teams. To address this, a web-based, guided interface has been developed to streamline the processing of Player Experience Inventory data. By utilizing an R-Shiny framework, the platform provides a structured, wizard-style workflow that manages essential data integrity tasks, such as handling missing values and performing normality checks, while generating exportable visualizations. The primary objective is to democratize data analysis, allowing practitioners to derive actionable insights without requiring advanced statistical expertise.

Formative and summative usability testing conducted with industry professionals confirms that the interface effectively supports both descriptive and inferential statistical workflows. Participants consistently valued the platform’s ability to simplify complex analytical processes within a professional game development context. However, the evaluation also revealed a critical tension in user experience design. While the platform successfully facilitates data interpretation, it achieved a System Usability Scale score of 64.5, indicating that the current implementation of explanatory text is suboptimal. Experts found the guidance repetitive, whereas novices occasionally felt overwhelmed by the volume of information provided.

These findings underscore a fundamental requirement for future iterations of research tools: the need to balance detailed instructional support with increased automation. To better serve a diverse user base ranging from statistical novices to seasoned researchers, interfaces must move toward adaptive guidance that scales based on user proficiency. Ultimately, the integration of such guided platforms represents a significant step toward improving the efficiency and reliability of user experience research, provided that the design remains flexible enough to accommodate varying levels of technical literacy.