Clinical Reality
Transforming skincare routines through data-driven personalization — an AI-powered skin analysis and loyalty tool for Clinique.
01 — Challenge
The Challenge
Clinique customers often feel overwhelmed by vast product lines and uncertain about which skincare routine actually works for their specific needs. The goal was to bridge the gap between product discovery and long-term brand loyalty through a personalized, tech-driven mobile experience.
02 — Research
User Research & Insights
I began by defining a primary persona to ground design decisions in a realistic user context.
03 — Design
Iterative Design Process
I moved from Task Analysis to Wireframing, focusing on a three-pillar user flow designed to take users from discovery to long-term retention.
During the wireframe phase, I prioritized the "Scan" interface, refining the user flow to include clearer instructional overlays. By simplifying the UI and adding real-time positioning cues, I ensured users could capture accurate data on the first try, reducing friction at a critical entry point.
04 — Testing
Testing & Validation
I conducted usability testing on the low-fidelity prototype to identify friction points, then improved and retested the high-fidelity prototype. Key Task: Complete the AI face scan and view personalized recommendations.
| Metric | Phase 1 — Low-Fi | Phase 2 — High-Fi | Improvement |
|---|---|---|---|
| Success Rate | 65% | 100% | +35% |
| Avg. Time on Task | 2m 14s | 48s | 64% faster |
| Miss-clicks (Errors) | 4.2 per user | 0.5 per user | 88% reduction |
| SUS Score | 62 — Marginal | 88 — Excellent | +26 points |
05 — Solution
The Solution
The final product is a sleek, clean interface that integrates three key capabilities:
