UX Research | Data & AI
Role: UX Research Intern
Timeline: May–December 2024
I joined IBM's Data & AI organization as a UX Research intern supporting watsonx BI, an emerging business intelligence product. My work focused on understanding the competitive landscape, evaluating dashboard experiences, and helping the product team make research-informed decisions about sharing, collaboration, and AI-powered features.
My research contributed to product direction for watsonx BI and helped identify opportunities within the competitive business intelligence landscape.
Key outcomes
Research findings helped inform the watsonx BI product roadmap.
A competitive feature comparison I created was used by IBM executives in official watsonx BI marketing materials.
My two research teammates and I were recognized as Q4 UXR Champions across IBM Software for our work on watsonx BI.
watsonx BI was still early in development when UX Research joined the project. Initial stakeholder research revealed an important knowledge gap: the team lacked a clear understanding of how competitors approached sharing and collaboration within business intelligence dashboards.
Without that understanding, it was difficult to identify where watsonx BI could differentiate itself.
Understand how competitors were implementing AI-driven editing, sharing, and collaboration features within the BI dashboard experience.
I began with secondary research to understand the business intelligence landscape and identify key competitors. From there, I conducted a competitive analysis of eight BI platforms, examining their strengths, weaknesses, opportunities, and approaches to dashboard sharing and collaboration.
The research was then narrowed to five primary competitors for a more focused feature comparison.
Secondary Research
Reviewed industry research, product documentation, and existing competitive intelligence.
Competitive Analysis
Evaluated eight competing BI products to identify patterns, gaps, and opportunities.
Feature Comparison
Compared 15 AI-driven editing, sharing, and collaboration features across five major competitors.
As patterns emerged from the competitive analysis, I developed a feature comparison chart examining 15 AI-driven editing, sharing, and collaboration capabilities across five major BI competitors.
Rather than simply documenting which features competitors offered, the comparison helped reveal areas where watsonx BI could differentiate its experience.
The chart became useful beyond the original research project: IBM executives later used my competitive feature comparison in official watsonx BI marketing materials.
The competitive research revealed meaningful differences in how BI platforms approached dashboard editing, sharing, and collaboration.
Three themes emerged:
1. Collaboration was inconsistent across competitors.
Sharing capabilities varied considerably, creating opportunities to rethink how users collaborate within a BI environment.
2. AI was changing the dashboard experience.
Competitors were beginning to incorporate AI-assisted functionality into traditional BI workflows, making it important to consider AI as part of the broader user experience rather than as a standalone feature.
3. Feature gaps created opportunities for differentiation.
Comparing competitors side-by-side helped the team identify areas where watsonx BI could distinguish itself instead of simply replicating established BI products.
Beyond the competitive evaluation, I supported additional research initiatives for watsonx BI throughout my six-month internship.
My work included research related to dashboard sharing and collaboration, configuration experiences, and other emerging product features. Across these projects, I worked with product and design stakeholders to identify research questions, conduct studies, synthesize findings, and communicate actionable insights to the broader team.
These experiences allowed me to contribute research at different stages of product development while working within IBM's larger UX Research organization.
Working on watsonx BI gave me the opportunity to conduct research within a complex, evolving enterprise product while collaborating with researchers, designers, product managers, and other stakeholders.
The experience strengthened my ability to translate broad product questions into focused research, synthesize complex information into actionable insights, and communicate findings in ways that could support product decisions.
Most importantly, I saw how research could extend beyond a final report. My work contributed to product discussions and roadmap decisions, and one of my competitive research artifacts ultimately found a second life outside the research team when it was used in IBM's watsonx BI marketing materials.
My research team was also recognized as Q4 UXR Champions across IBM Software for our contributions to watsonx BI.
