GoCanvas Projects
I assisted with several projects while at GoCanvas to develop skills in UX Research. This page highlights the skills I learned and applied through assisting on those projects.
Survey analysis.
Survey
The Lead UX Researcher created and sent a survey to hundreds of GoCanvas users to gather data on how their industry, number of employees, and other information on how they use GoCanvas.
Dashboard
I created a dynamic dashboard in Google Sheets. Industry type is selected at the top of the page, which then displays a bar graph on primary usage types depending on the industry selected. Counts on GoCanvas uses such as checklists, daily logs, and other forms are displayed and updated underneath the bar graph.
User Testing. Qualitative Analysis. Synthesis.
During my time at GoCanvas working once a week under the Senior UX Researcher, I took notes in Lookback, coded qualitative data in Dovetail, as well as wrote Insight articles in Dovetail that were shared to internal stakeholders to highlight our weekly user research findings.
Note-taking.
Lookback interface where I would take notes.
In Lookback, I took notes on participant's reactions, actions, words, task completions, and other notable items during user testing.
I then would rewatch the video and edit/update notes to underscore other notable behaviors I may have missed during the initial session.
Qualitative coding.
I copied the notes I took in Lookback and pasted them into Dovetail so I could code them based off behavior, reactions, points of confusion, task completion, and other patterns.
Qualitative coding data organization.
Qualitative coding can be a little overwhelming. Here are some of the ways I organized qualitative codes to facilitate analyzing and later on synthesizing the data.
A/B testing.
For A/B Testing, participant codes would be separated into two groups depending on the condition they were a part of. I would analyze the data separately and then compare the tags between both of the groups.
Within each participant block, I would separate the codes with areas of interest selected prior to the user testing depending on our research question. Other times, overarching patterns would emerge and I would make a block for that category with corresponding codes supporting that category.
Coding analysis.
To analyze the codes while preparing to synthesize the data in Dovetail Insights, I would track the number of Dovetail codes using the analysis tool. I would include the highest number of tags per code in the Insights articles and would toss out codes that were only used a few times.
Coding synthesis.
I would then compile the analyzed data into actionable insights and learnings from the research shared in an article format in Dovetail, which would then be accessible to my colleagues. I would include specific instances of an observed behavior, actual quotes from participants, and provide analysis for why the behavior occurred.
Observation tags.
In the Insight article, I included the code and its associated observations so that when readers clicked the code, they could see what other observations are linked to the selected code.
Readers can also see the number of times a code appears in an analysis.
Recommendations.
We would then provide actionable recommendations for the dev team or other relevant stakeholders to perform based off the analyzed and synthesized qualitative data.
