Mind the Gap Between UX Data and Visualization Proposals: Analyzing User Dissatisfaction and Driving Interactive System Improvements

Maylon Macedo; Luciana Zaina

doi:10.5753/jbcs.2026.5741

Authors

Maylon Macedo Aeronautics Institute of Technology (ITA) https://orcid.org/0000-0002-2686-1103
Luciana Zaina Federal University of São Carlos (UFSCar) https://orcid.org/0000-0002-1736-544X

DOI:

https://doi.org/10.5753/jbcs.2026.5741

Keywords:

User eXperience, UX data, Visualization, IHC

Abstract

Software professionals typically analyze user experience data (i.e., UX data) to identify positive and negative aspects of user interactions with software. While the scientific literature has proposed various UX data visualization approaches, these methods are rarely evaluated by software professionals (i.e., designers and developers) to determine their practical effectiveness in understanding user satisfaction and dissatisfaction. Moreover, professionals often adapt visualization techniques based on their own practical experiences, contributing to a wealth of informal knowledge published in UX blogs and websites (known as grey literature). To consolidate this dispersed knowledge, we conducted an analysis of 144 grey literature articles that discussed UX data definitions and visualization techniques. Our findings revealed three key components that support the investigation of user dissatisfaction: the visualization approach, the purpose of using the visualization, and UX data definitions. To validate the relevance of this three-leg approach, we conducted a study with 31 software professionals, using five UX data visualizations focused on a mobile airline ticketing application. We selected this domain to ensure familiarity and minimize the need for contextual interpretation. Through an online questionnaire, participants provided insights on how well the visualizations helped them identify aspects of the application contributing to user dissatisfaction. The results confirmed the practical value of the three-leg approach, with 78% of positive feedback regarding its effectiveness in UX data analysis. Additionally, 84% of participants acknowledged that the proposed visualizations could be integrated into their daily workflows. In this extended study, we introduced a new research question (i.e., RQ3) to investigate how UX data visualizations can support system improvements beyond identifying dissatisfaction. To address this, we conducted a new analysis of the grey literature, focusing on the potential benefits that UX data visualizations can bring to interactive systems. We also reanalyzed the collected study data, incorporating participant comments on how UX data visualizations could enhance software development processes. The comparison between the new findings and participant feedback highlighted four key themes: understanding users, improving system interaction, fostering self-knowledge about the system, and handling development resources efficiently. These insights reinforced the role of UX data visualizations in bridging the gap between theoretical models and practical applications for software professionals. Our findings update prior conclusions and discussions, demonstrating the broader impact of UX data visualizations beyond dissatisfaction analysis, extending to strategic decision-making, usability improvements, and software evolution.

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