Mixed methods design research for IBM's enterprise AI studio
TIMELINE
Present
ROLE
UX Researcher
TEAM
3 researchers
1 research lead
SKILLS
UX Research
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This page contains only a high level view into my work, but I'm happy to chat! Please get in touch for a deeper look into my research case studies.
01 — OVERVIEW
My role as a UX Researcher
IBM watsonx.ai is an enterprise-ready AI developer studio for new foundation models, generative AI, and traditional machine learning. It allows enterprises to train, validate, tune, and deploy both traditional and foundation models.
I work with PMs, developers, and designers to identify and address research opportunities across different work streams in watsonx.ai. I execute end-to-end mixed methods research and deliver actionable insights and recommendations that influence the product roadmap and improve user experiences.
02 — RESEARCH PROCESS
My research process
Scope down the research request
Identify key research questions and goals
Align with product, design, and engineering teams on priorities and target users
Collect assumptions
Define success metrics
Develop a timeline and expected deliverables
Plan and prepare the materials
Draft and iterate on the study protocol, discussion guides, and tasks
Develop screeners and recruit participants
Loop in stakeholders for alignment, feedback, and buy-in
Conduct the research
Schedule and facilitate sessions
Capture qualitative insights
Gather quantitative data
Synthesize the data and produce insights
Collect raw data from transcripts
Identify patterns using affinity mapping to create themes
Cross-reference findings with analytics or supplementary data
Develop insights and recommendations rated by severity or risk
Share and discuss next steps
Present actionable recommendations to stakeholders
Collaborate with designers and engineers to implement changes
Discuss feasibility and impact of addressing recommendations with stakeholders
Document and trace impact
Document insights in research repository
Track usability improvements and measure post-research success
Socialize results post-research to relevant channels and on a rolling basis to support parallel efforts
03 — IMPACT
My impact at a glance
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Conducted 5 evaluative studies across 3 product features in contribution to an iF Design Award for UX Design
Read the article ↗
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Coached team of 8 developers on enterprise design thinking for IBM Canada’s early career program
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Research playback decks viewed by 1000+ IBMers
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Represented the Data & AI business unit (400+ designers) during the Q3 Quarterly Design Review to present research to 7 cross-org Product Design VPs
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Influenced the design of new IBM Carbon for AI design system components
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Led a long term research program with content design to produce 4+ new sections of AI documentation
04 — PROJECT SUMMARIES
Snippets of selected research projects
05 — RETROSPECTIVE
What I am learning
Planning a research study is a research study itself.
Sometimes product teams don't know what they want to know, and that's perfectly fine. It's an exercise in itself to ask effective questions and work with teams to understand what unanswered questions exist and what research would be most impactful. This collaborative planning phase ensures alignment and maximizes the effectiveness of the research.
Impact requires visibility
Research doesn’t end at the final playback. Proactively sharing what has been learned even after the formal sessions are done ensures that the work continues to create value. There’s always someone who can benefit from what has been uncovered, and letting that work sit untouched means missed opportunities for impact.