GLP-1 Meal Prep Platform
Mealcycle: Designing a GLP-1 Patient Experience from First Click to Ongoing Care
Role
Product Design Lead
Timeline
Concept → MVP Lovable Prototype (6 weeks)
Impact
User Testing Onboarding Completion 89%
Patient-Facing Intake Flow
I designed a multi-step onboarding wizard that reflects medical intake best practices:
Step 1: Medication Selection
Step 2: Dosage Stage
Step 3: AI-Based Plan Calculation
Simulated calculation → protein targets and macro guidance
Why this matters for EllieMD:
This framework translates directly into:
Medical intake flows
Treatment selection journeys
Prescription onboarding
Sensitive health disclosures
I prioritized:
Progressive disclosure
Reduced cognitive load
Reassuring copy
Clear progress indicators
Mobile optimization
Account & Dashboard Experience
Weekly Plan View
Each meal card includes:
High-protein labeling
Macro visibility
Digestibility tags (anti-nausea, low GI)
Clean, scannable layout
Design focus:
Information hierarchy
Digestible medical content
Trust-building clarity
Usability Testing Results
Task 1: Start and Complete Onboarding | Task 2: Find Help for Nausea |
|---|---|
Success Rate (Round 1 prototype): Drop-off Points:
After iteration:
Success Rate (Round 2): Time to completion decreased from: | Prompt: Round 1:
After repositioning assistant + label update: Round 2:
|
Metric | Before Iteration | After Iteration |
|---|---|---|
Onboarding Completion | 62% | 89% |
Avg Completion Time | 4m 12s | 2m 38s |
AI Assistant Discovery | 28% | 83% |
Reported Trust Score (1–5) | 3.2 | 4.6 |
Emotional Impact Metrics
We asked: “How confident do you feel managing nutrition on GLP-1 after using this?”
Before experience: Average: 2.9 / 5
After prototype interaction: Average: 4.4 / 5
Participants said:
“This feels made for me.”
“Finally something that understands GLP-1.”
“I feel less anxious about muscle loss.”
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