80%
Onboarding completion
Up from 40%
Data-DrivenSports AnalyticsPlatform
Transforming raw sports data into actionable insights - a SaaS platform redesigned from scratch to improve usability, engagement, and free-to-paid conversion.
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Impact & Outcomes
7.7K
Tracked events
Across product interactions
100%
Navigation clarity
User testing
7m 37s
Average engagement
Post-launch GA
The Problem
Complex, unstructured data driving users away
User Problem
Sports analysts struggled with complex, unstructured data that was hard to navigate and interpret.
- Data scattered across multiple sources
- No clear visual hierarchy
- Difficult to find actionable insights
Business Goals
Build a 0→1 product that converts free users into paying subscribers.
- Improve usability and engagement
- Reduce drop-off during onboarding
- Increase conversion to paid subscriptions
Constraints
⚡ No existing design system
⚡ Tight timeline for MVP launch
Success Metrics
📈 User retention rate
📈 Free-to-paid conversion rate
Design Process
Five phases from research to release
- User interviews revealed analysts felt overwhelmed by data complexity
- Identified 3 user archetypes: casual fans, serious analysts, and professionals
- Competitive analysis: rivals had robust data but consistently poor UX - clear differentiation opportunity
Users don't understand some of the data points.
- Visual hierarchy matters more than feature breadth at this stage
- Onboarding is the critical conversion window
- Free trial must demonstrate value before asking for payment
No existing design system - built from scratch.
- Onboarding: users didn't understand platform structure → Added guided product tour with contextual tooltips
- Navigation: hard to find data across multiple leagues → Redesigned nav for multi-league scalability
- Subscription: users hesitant to commit without trying → Free trial offer gating key features
Primary flow: Landing → Sign Up → Onboarding → Dashboard → Explore → Subscribe.
- 3 rounds of wireframe revisions based on stakeholder feedback
- Clickable Figma prototype: dashboard with realistic data, onboarding flow, subscription flow
- 8 users tested - tasks: complete onboarding, navigate leagues, understand subscription
100% of testers found target data without assistance after nav redesign.
- Added contextual tooltips based on GA event tracking data
- Used a mix of qualitative and quantitative research to understand pain points and run usability tests
- Continued tracking sessions, events, and page performance to inform each design iteration
The redesign measurably improved usability, engagement, and business metrics.
Process in Pictures
From research to refined interface
Initial data from stakeholders
Complex, Unstructured Data
User Flow Mapping, Primary flow
Landing → Onboarding → Dashboard → Explore Data → Subscribe
Initial Wireframes
3 rounds of wireframe revisions based on stakeholder feedback
Interactive Prototype
Clickable Figma prototype with realistic analytics data
Dashboard UI - shipped to production
Detailed design specs for a multi-league sports analytics platform, covering component behaviour, tooltip logic, responsive layout, and guided onboarding.
Problem → Solution
Every friction point addressed
Information Architecture
✕
Data scattered across sources
✓
Unified dashboard with single source of truth
Visual Design
✕
No clear visual hierarchy
✓
Typography scale + card-based layout system built from scratch
UX Writing
✕
Difficult to find actionable insights
✓
Contextual data highlights and smart tooltips
Conversion
✕
High drop-off during onboarding
✓
Guided product tour - value shown before paywall
Responsive Design
✕
Poor mobile experience
✓
Responsive redesign after 42% mobile usage identified
Monetisation UX
✕
Users hesitant to subscribe
✓
Free trial with feature preview, not a hard gate
Results
Measurable improvement across every metric
Onboarding Completion
+100%Before (Round 1)40%
After (Round 3)80%
User Retention
+81%Before (Round 1)32%
After (Round 3)58%
What's Next
New features in development
The product continues to evolve through ongoing feature launches, testing, and iteration based on user feedback and product data.
In Testing
Historical Data Platform
An upcoming analytics feature that lets users explore historical game performance using team selection, flexible time ranges, and advanced filters. It helps users quickly uncover trends across past results and compare performance under specific conditions.
Currently being validated before release
Design Philosophy
What guides every decision
01
Clarity Over Complexity
Simplify complex systems through clear information architecture and visual hierarchy.
02
Data-Informed, Not Data-Driven
Use metrics to validate decisions, but always prioritise user needs over numbers.
03
Design for the Edge Cases
How a product handles failure defines its quality more than happy paths.
04
Iterate, Measure, Refine
No design is perfect on the first try. Ship, learn, improve — then repeat.
My Contribution
Full ownership from idea to launch
Product Strategy
Defined product structure and UX strategy aligned with business goals
End-to-End Design
Designed the full user experience and interface — lo-fi to hi-fi
Product Direction
Collaborated on feature prioritisation and roadmap decisions
IA & Data Architecture
Established information architecture and data presentation strategy
User Testing
Recruited and moderated 3 rounds of usability testing with 8 participants each
Analytics Setup
Set up Google Analytics event tracking to inform post-launch iterations
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