CareMatch

CareMatch

Less Guess, Better Care

Less Guess, Better Care

Role: UX Designer

Role: UX Designer

Timeline: 6 Weeks

Timeline: 6 Weeks

Tools: Figma

Tools: Figma

The Problem

Families face extreme anxiety when selecting home caregivers. Existing platforms only display qualifications and ratings, but cannot verify the caregiver's true character and reliability, leading families to feel that the entire matching process is "like a lottery."

Key Pain Points:

AI Black Box

AI Black Box

Credential vs. Character

Credential vs. Character

Monitoring Dilemma

Monitoring Dilemma

Screening Fatigue

Screening Fatigue

Feedback Gap

Feedback Gap

Research

Methodology: Double Diamond
- Secondary research + competitive analysis (Cera Care, Homage, Care.com, Onihelp)
- 5 in-depth interviews with family decision-makers

"Users perceive caregiver screening as a lottery — the hidden algorithmic logic creates black-box anxiety."

Solution 1

AI Explainability Cards

AI Explainability Cards

Solution 2

Personality Profiling via SJT

Personality Profiling via SJT

Solution 3

Non-invasive Care Diary

Non-invasive Care Diary

Solution 4

Closed-loop Feedback

Closed-loop Feedback

Iteration 1: Internal Pilot

Round 1

Complex transitions caused hesitation. Core features weren't prominent enough.

→ Simplified navigation, reduced information density

Iteration 2: External Testing (5 participants)

Round 2

Button logic confused users. Detail page was too cluttered.

→ Restructured information hierarchy, added match rate data

Iteration 3: Expert Review

Round 3

Matching engine lacked transparency.

→ Added dual-sided onboarding + Situational Judgement Tests for caregivers

Final Product

The final CareMatch product offers streamlined navigation, step-by-step guidance, and a comfortable user experience focused on delivering relevant care options efficiently.

Large preview image above demonstrates the clean interface and clear call-to-actions designed for minimal cognitive load.

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