SaaS Platform Design + AI-enabled Logistics System
AeroTrack
Project Information
AI-enabled logistics management service
Sep – Nov 2024
UX Research, UX Designer
Challenge
Small importers and exporters struggle with fragmented communication, inconsistent document requirements, and limited visibility across logistics partners.
With information scattered across emails, PDFs, and separate portals, shippers face delays, unexpected costs, and repeated data entry throughout the import/export workflow.
Solution
Standardized Documentation: Designed a template-based document system that auto-generates export/import forms, reducing redundant manual work and preventing submission errors.
Real-time Tracking Dashboard: Built a unified tracking interface integrating shipping line data, carrier updates, and landing-point events—helping users identify issues early.
Group Shipment Matching: Created an AI-driven matching system that groups shippers with similar schedules, enabling cost-efficient consolidated shipping.
AI-Supported Communication: Introduced chatbot guidance and contextual tooltips to clarify next steps, simplify decision-making, and reduce dependency on logistics experts.
Impact
Reduced document preparation time via template automation.
Increased shipment visibility and issue detection through real-time tracking.
Lowered logistics costs for small shippers through group-matching services.
Market Context & Research
Market Context
The global air cargo transportation market is experiencing substantial growth, with post-pandemic e-commerce demand breathing new life into the air freight industry.
E-Commerce Growth
Global e-commerce is set to grow 14% over the next five years, presenting a vital opportunity for the air cargo industry. The sector is projected to grow from $3.5 trillion in 2022 to $7 trillion by 2025, representing 16% of total air cargo operations.
Regional Distribution (2022):
Asia: $2.09K billion
America: $1.13K billion
Europe: $828.3 billion
Oceania: $52.9 billion
Africa: $43.9 billion
User Research
Information Flow Analysis
Through comprehensive mapping, I identified a complex ecosystem involving 9 distinct stages with 10 information exchanges—the majority representing redundant data transfers.
In-depth interviews
Conducted 40-minute in-depth interviews with 2 forwarding industry professionals:
Small handicrafts individual importer
Clothing vendor company employee
Key Findings (User Difficulties)
Design Solution
Feature Strategy
User Personas
Design Process
Mapped the entire service ecosystem to identify connections between user touchpoints and internal systems.
Key Flows:
Sign Up → Document Creation → Group Matching → Tracking → Payment
Backend integration with Carrier DB, Message DB, Shipping Schedule DB
Real-time encryption for secure data exchange
Main Features:
Comprehensive Data Collection - Automated templates, AI review, document storage
Real-time Tracking System - Map-based UI, status alerts, carrier communication
Optimizing Shipping Costs - AI matching, group shipment, split payment
Integrated Communication - Chatrooms, notifications, stakeholder coordination
Translated service flows and IA structure into low-fidelity wireframes to define screen hierarchy, user actions, and core interactions across the platform.
The wireframes focused on clarity, reducing cognitive load, and ensuring each step supports progress through the logistics workflow.
Design Iteration (Wireframe → User Testing → Final Design)
Initial Wireframe
Created low-fidelity wireframes for 4 core features:
Dashboard with delivery overview
Document creation flow
Group shipment matching
Tracking interface
UX Strategy Applied:
UI: Visual hierarchy prioritizing critical information
Usability: Intuitive understanding of complex finance/logistics concepts
Psychology: Build trust through clear, accurate information
User testing
Tested wireframe prototypes with target users and collected feedback
Dashboard
❌ "Need clearer guidance for beginner shippers"
❌ "What are the next steps after viewing status?"
Iteration:
Added step-by-step guidance and next action prompts
Document
❌ "AI review button not clearly visible"
❌ "Cargo list hard to scan at a glance"
Iteration:
Auto-expand AI review when issues detected, improved information hierarchy
Tracking
❌ "Logistics notifications not prominent enough"
❌ "Hard to understand current status at a glance"
Iteration:
Added intuitive tooltips, prominent alert system
Final Design
Key Design Decisions
1. AI-Powered Document Review
Why: Reduces compliance errors and saves time on repetitive checks
How: Auto-validates against regulations, flags issues with explanations
Impact: Estimated 40% reduction in document preparation time
2. Map-Based Tracking Interface
Why: Builds trust through visual confirmation of shipment progress
How: Real-time location updates with status alerts at each waypoint
Impact: Reduces stakeholder communication overhead
3. Group Shipment Matching
Why: Enables small shippers to access bulk shipping rates
How: AI matches shippers based on route, timing, and cargo requirements
Impact: Cost savings through container space optimization
4. Integrated Communication Hub
Why: Centralizes fragmented stakeholder communication
How: Dedicated chatrooms for each shipment with all parties
Impact: Creates accountability and reduces email chaos
Dashboard
Design Decision: Map-based interface builds spatial understanding and trust in real-time location data
Key Improvements:
Central world map with real-time route visualization
Shipping information panel with quick-scan layout
Bottom cards showing: Shipment Issues | Payment | Calendar
Clear next-step guidance for beginners
My Document
Design Decision: Automated validation reduces human error and speeds up repetitive documentation tasks
Key Improvements:
AI Document Review auto-expands with issue explanations
Visual validation checkmarks for completed sections
Warning badges for critical items (e.g., "Fragile packaging required")
One-click document retrieval and reuse
Group Shipment
Design Decision: Transparent cost savings motivates group participation and builds platform value
Key Improvements:
AI-recommended groups prominently displayed
Clear cost comparison: Individual vs Group pricing
Filter tags showing: Date, Nearby, Ratings, Insurance
Visual route cards with departure/arrival times
Tracking
Design Decision: Visual status progression reduces anxiety and need for stakeholder communication
Key Improvements:
Interactive map with origin → current location → destination
Floating shipment info card with collapsible details
Status timeline: Pending → On-Airway → Customs → Delivered
Red alert badges for urgent issues
Result & Impact
Validated Through Testing
User-friendly experience confirmed across 3 testing rounds
Pain point resolution validated for all 3 core problems
Feature adoption positive feedback on AI review, group matching, real-time tracking
Expected Business Impact
Faster document preparation through templates and AI
Cost savings for small shippers through group purchasing
Reduced errors via automated compliance checking
Improved transparency through real-time tracking and integrated communication
Reflection & Learnings
What I Learned
1. Complex B2B flows require extensive user research
Mapping the 9-stage information flow with 10 exchanges was crucial to understanding redundancy
2. Iteration is essential for trust-building features
Payment and tracking features needed multiple rounds to get the transparency right
3. AI as assistant, not replacement
Users wanted AI to flag issues and suggest solutions, not make decisions for them
If I had more time, I would:
Conduct testing with actual carriers and customs brokers
Explore a mobile-first experience for on-the-go tracking
Develop an onboarding flow specifically for first-time international shippers
Expected Business Impact
Faster document preparation through templates and AI
Cost savings for small shippers through group purchasing
Reduced errors via automated compliance checking
Improved transparency through real-time tracking and integrated communication