(01) CASE STUDY
Data Visualization & BI Reports
Lead Designer — AI Product Design & Research | Enterprise BI & Analytics
Driving User Adoption Through Data Visualization & AI-Driven Insights
A strategic initiative focused on improving user adoption of enterprise BI tools by redesigning dashboards, clarifying data narratives, and integrating AI-assisted research and validation methods.
2021-2024
Tilda Publishing
YEARS
Lead UX Designer
ROLE
Tools
Tools
Product Teams from Kantar Group ( XTEL, VR, Richmix, IQ)
TOOLS
TEAM
(02) MY ROLE
My Role
As Lead Designer in AI Product Design & Research, I led a redesign initiative focused on:
- Improving clarity and usability of analytical dashboards
- Increasing adoption across hierarchical user roles
- Aligning visualization logic across modules
- Integrating AI-driven research insights into prioritization
(03) OVERVIEW
Project Summary
The Challenge
Enterprise users relied heavily on TPM analytics and BI dashboards to make high-impact financial and commercial decisions. However, low adoption rates, cognitive overload, and inconsistent data visualization patterns reduced effectiveness.
- Low user adoption of reporting and BI modules
- Overloaded dashboards with poor visual hierarchy
- Inconsistent chart logic across modules
- Misalignment between business KPIs and UI presentation
- Limited understanding of how different personas consumed analytical data
- Need to align business KPIs, user goals and design strategy across multiple stakeholders.
(04) PROJECT GOALS
Goals
Improve clarity and readability of analytical data
01
Support faster and more confident decision-making
02
Standardize visualization patterns across the product
03
Increase user adoption and adoption value
04
(05) APPROACH
AI-Enabled Research & Insight Generation
To understand adoption barriers and decision behaviors, I integrated AI tools into the research workflow:
- Accelerated interview analysis and insight clustering across enterprise stakeholders
- Combined qualitative findings with product adoption data and usage analytics
- Identified behavioral patterns across hierarchical roles
- Applied AI-assisted benchmarking to evaluate visualization standards
- Reduced discovery uncertainty and improved prioritization accuracy
(06) PROCESS
Process
- Discovery & Data AuditAnalyzed adoption metrics, usage tracking, and reporting inconsistencies.
- Persona & Role MappingDefined analytical needs per hierarchy level using AI-supported synthesis.
- Visualization Framework RedesignSimplified chart types, reduced redundancy, and established hierarchy principles.
- Wireframing & Validation in FigmaExplored multiple navigation and layout scenarios; validated with stakeholders.
- Iteration & Adoption MonitoringContinuously refined dashboards based on feedback and performance indicators.
(07) DELIVERABLES
Key Deliverables
Established standardized visualization principles across modules
Scalable Product Design & Visualization Systems
01
Created reusable dashboard components within the design system
02
Organized structured Figma libraries and documentation
03
Ensured governance models for long-term consistency
04
Balanced flexibility for customization with system-wide coherence
05
Key Deliverables
- Redesigned BI dashboards with improved visual hierarchy
- Standardized chart framework (bar, line, waterfall, variance logic)
- Role-based analytical views
- Design documentation and governance guidelines
- AI-supported research synthesis report
(08) VISUAL GALLERY
Visual Gallery
“
Clear data creates confident decisions. Structured design turns complexity into insight.
(09) IMPACT
Results & Outcomes
While specific metrics remain confidential, the initiative:
-
Increased clarity and trust in analytical tools -
Improved adoption across key enterprise roles. -
Reduced cognitive load in data-heavy environments -
Strengthened alignment between business KPIs and product interface -
Enabled scalable dashboard development through reusable components
(10) REFLECTION
Key Learnings
This initiative strengthened how the organization approaches data-intensive product design. By integrating AI-assisted research, structured visualization systems, and validated Figma delivery workflows, we built a foundation for scalable, insight-driven enterprise experiences.
- Data visualization is not decoration — it is decision architecture.
- AI accelerates synthesis, but strategic judgment drives clarity.
- Adoption improves when insights match role-specific mental models.
- Enterprise complexity requires structure, governance, and alignment.
