"Merging Results Is No Easy Task": An International Survey Study of Collaborative Data Analysis Practices Among UX Practitioners

TL;DR

This survey study explores international UX practitioners' collaborative data analysis practices, highlighting common modes, challenges faced, and implications for designing better support tools for teamwork in usability testing.

Contribution

It provides the first large-scale international survey on collaborative data analysis practices among UX practitioners, revealing common collaboration modes and key challenges.

Findings

Practitioners often work under time pressure.

Three main collaboration modes identified.

Major challenges include resource constraints and merging analyses.

Abstract

Analysis is a key part of usability testing where UX practitioners seek to identify usability problems and generate redesign suggestions. Although previous research reported how analysis was conducted, the findings were typically focused on individual analysis or based on a small number of professionals in specific geographic regions. We conducted an online international survey of 279 UX practitioners on their practices and challenges while collaborating during data analysis. We found that UX practitioners were often under time pressure to conduct analysis and adopted three modes of collaboration: independently analyze different portions of the data and then collaborate, collaboratively analyze the session with little or no independent analysis, and independently analyze the same set of data and then collaborate. Moreover, most encountered challenges related to lack of resources, disagreements with colleagues regarding usability problems, and difficulty merging analysis from multiple practitioners. We discuss design implications to better support collaborative data analysis.