Case Study
OneCub
Data Privacy & Analytics Dashboard
Executive Summary
Redesigning complex carbon footprint and personal spending data into scannable user dashboards.
OneCub is a Paris-based data analytics platform that empowers users to regain control over their personal digital footprint and online spending. The startup engaged me to overhaul their existing interface, transforming dense statistical data (travel mileage, carbon emissions, shopping histories, and connected accounts) into scannable visual dashboards.
Client Feedback
Sky knows exactly how startups operate and we have been able to talk at a very high level about our tech and product requirements. Sky made strong UX propositions and worked closely with us to create a great product.
The Challenge
Overcoming information overload
The initial OneCub dashboard suffered from cluttered navigation, wall-of-text explanations, and unorganised metrics. Users found it difficult to quickly parse their environmental impact (kg eq CO₂) versus personal spending across high-tech, travel, and retail categories.
How do you convert multi-category personal data into clear, actionable dashboard visual cards without overwhelming everyday consumers?
Dashboard UX & Visual Design Transformation
I restructured the legacy layout into a modular grid featuring high-contrast stat cards, clear categorical breakdowns (Shopping, Travel, Sport), and peer benchmarks:
- Legacy Analysis: Replaced text-heavy promotional blocks with high-impact data visualisation.
- Modular Category Cards: Designed intuitive metrics comparing personal consumption directly against community averages (e.g., 3,195 km distance vs. average 1,945 km).
- Carbon Footprint Metrics: Prominently displayed total global carbon impact (10 kg eq CO₂) alongside per-kilometer calculations (3 g/kg eq CO₂).
Frictionless Onboarding & Account Connection Flow
To increase conversion and platform retention, I designed a 3-step progressive onboarding sequence:
Fast account creation with clear privacy guarantees.
Visual connection matrix supporting major platforms (Amazon, eBay, Cdiscount, UEFA, Sncf).
Automated scanning UI reassuring users about encrypted data handling.
Strategic Takeaways
Key learnings from the build
Data Humanisation
Translating raw mathematical outputs into relatable units (kg eq CO₂ per km) drives consumer comprehension and habit loop engagement.
Progressive Disclosure
Breaking down complex setup flows into small, transparent steps boosts user activation and trust during data connection.
Peer Benchmarking
Comparing user metrics directly against community averages provides instant context and encourages carbon reduction behaviours.
Tools & Software
What powered the build
UX & Prototyping
Visual Design