UXPA Boston 2018: Using Qualitative Data Analysis Software (QDAS) to create a virtual tapestry of your organization's UX research

Presented by Stuart Robertson & Kay Corry Aubrey

Overview of software

• Capture the complete picture
• Find patterns and trends
• Some data is quantitative…
  • Task completion
  • Usability scores
  • Completed purchases
• …but most UX research is qualitative
  • Emotional reactions
  • The “why” behind the data
  • Richer understanding of complexity
• QDAS helps you…
  • organize qual and match against the quant
  • incorporate media (photos, videos, transcripts, tweets)
  • look at data through different lenses
  • simplify storage/access to data
  • facilitate teamwork
  • help interpret through visualizations

Why use?

• If you have longitudinal studies, are tracking users over time, and building upon research over time
• Analyze and synthesize large amounts of info with more rigor than paper
• Insights to build UX research deliverables come from many data sources, in many digital formats
• Easier to repurpose data for use in other project
• Paper has short shelf-life, destined for recycle bin
• Organize & code qualitative data, with easy access to primary source
• Start with paper (e.g. to do an affinity diagram) and then transfer to QDAS for permanent record

Case study

• Field study to test media device in Mormon congregations worldwide
• Transcriptions into NVivo, coded
• Created info architecture of research, connected to primary sources
• Added annotations/reflections, to see thought process of research team over time
• Final analysis done in two days (rather than several weeks) because data was so well organized

Key features

• Many vendors, pick one that best suits your project
• Code/tag data (e.g. tied to timestamp in audio/video)
  • Very powerful to hear people talk about issues in their own voices
  • Explore with text mining tools… word trees, word frequency, word cloud
• Organize (and later reorganize) codes/tags into relevant groupings
  • Organized codes become an outline that ultimately structures a research report (!)
• Crosstab query… e.g. see codes by demographic breakdown, then drill into source data
• Pull in data from social media…
  • geographic distribution
  • cluster analysis
  • sentiment analysis

Questions

• distributed usage over the web?
• options for open source projects?