iCoffee
Role
UX/UI Designer (Sole Designer)
Services
App Design
Branding
Mobile App
Industry
Food and Beverage
Date
4 Weeks
Tools
Figma
FigJam
Adobe Photoshop
Project Overview
Optimizing High-Volume Coffee Ordering for Time-Critical Teams
Summary
iCoffee is a productivity-focused mobile ordering assistant designed to support urgent, complex, and high-volume coffee orders. The project explores how structured ordering, advance scheduling, and clear confirmation flows can reduce friction for busy professionals and teams who rely on timely, accurate coffee pickup to support their daily operations. The goal was to design an experience that minimizes wait time, prevents order errors, and enables reliable coordination between users and selected coffee branches.
The Problem
Busy professionals and corporate teams frequently place large or complex coffee orders under time pressure. Traditional in-store ordering and fragmented mobile experiences often result in long wait times, miscommunication, and order inaccuracies—especially during peak hours.
Users struggle with:
• Placing multi-item or team orders accurately
• Coordinating pickup times with busy schedules
• Selecting a specific branch for large orders
• Avoiding delays, queues, and order mistakes
These challenges introduce unnecessary friction into otherwise simple productivity routines.
Goals & Success Criteria
The primary goal of iCoffee was to support time-critical ordering without sacrificing accuracy or user confidence. The product aims to transform coffee ordering into a predictable, low-effort task that fits seamlessly into professional workflows.
The core goals were to:
• Enable users to submit complex and high-volume orders with confidence
• Allow users to select a preferred branch for pickup
• Support scheduled pickup times to reduce waiting and coordination friction
• Minimize order errors through clarity and confirmation
• Create a fast, intuitive flow optimized for productivity
Success was measured by users’ ability to complete large or scheduled orders quickly, accurately, and without uncertainty.
Research & Key Insights
To better understand user needs and frustrations, I conducted qualitative research through interviews and surveys focused on coffee ordering behavior during busy workdays. The research aimed to uncover where time, clarity, and trust were being lost in existing ordering experiences.
Key Insights
• Users feel stressed when placing large or detailed orders under time pressure
• Order accuracy becomes more critical as order size increases
• Waiting in line significantly disrupts professional schedules
• Users value advance ordering and predictable pickup timing over customization depth
These insights informed all major decisions related to flow structure, confirmation, and scheduling.
User Personas
Based on the research findings, I created two primary personas representing users who rely on coffee ordering to support productivity under time pressure—both for individual use and for team coordination.
These personas helped anchor design decisions around speed, accuracy, scheduling, and confidence throughout the ordering and pickup experience.
Caitlin Chen
Caitlin is a productivity-focused business owner who frequently places complex, multi-item coffee orders under tight schedules. She needs a reliable way to submit orders in advance, select a specific branch, and schedule pickup times so she can avoid waiting in line and maintain control over her workday without interruptions.
Kimball Cho
Kimball is an anxious intern responsible for handling large, detailed coffee orders for his team. He operates under pressure and cannot afford order errors or delays. He needs a structured, high-accuracy ordering system that clearly confirms items, quantities, pickup location, and timing to ensure flawless execution.
User Flow
To ensure a smooth and predictable experience, I mapped the core user flow from order creation to scheduled pickup. This helped identify unnecessary steps and areas where users needed reassurance before committing to large orders.
The primary flow focused on:
• Browsing and selecting multiple items
• Choosing a branch location
• Scheduling a pickup time
• Reviewing and confirming order details
Wireframes
Low-fidelity wireframes were created to explore layout, information hierarchy, and flow logic before visual design. This stage allowed rapid iteration and ensured the experience supported clarity under time pressure.
The wireframes focused on:
• Clear item grouping and quantities
• Strong confirmation and review states
• Minimal friction between steps
• Fast navigation for repeat actions
Visual Design & UI System
After validating the structure, I developed a visual system that emphasized clarity, trust, and efficiency. The UI was designed to reduce anxiety during ordering while maintaining a modern, professional tone.
The design system includes:
• Typography optimized for readability under speed
• A calm, trustworthy color palette
• Consistent buttons and input components
• Clear order status and confirmation indicators
Final Design Solution
The final high-fidelity design delivers a streamlined ordering experience tailored to high-volume and scheduled use cases. The interface prioritizes clarity at every step, ensuring users feel confident before placing and retrieving their orders.
Key Features
• Structured flow for complex and team orders
• Branch selection and scheduled pickup timing
• Clear order review and confirmation states
• Minimal distractions to support fast decision-making
Usability Testing & Iteration
Usability testing was conducted using an interactive prototype to evaluate order clarity, scheduling confidence, and error prevention. Feedback highlighted the importance of strong confirmation steps and visibility of pickup details.
Based on testing feedback:
• Order review screens were refined
• Pickup time and branch selection visibility was improved
• Confirmation messaging was clarified
These iterations reduced uncertainty and improved overall confidence in placing large orders.
Outcomes & Learnings
Outcomes
• Improved confidence in high-volume ordering
• Reduced perceived risk of order errors
• Clearer coordination between users and pickup locations
Learnings
• Scheduling is as important as speed in productivity tools
• Confirmation states play a critical role in reducing anxiety
• Designing for team workflows requires precision and clarity
This project reinforced the importance of designing for real-world time pressure and operational reliability.
Next Steps
If the project were to continue, future improvements would include:
• Saved team orders and templates
• Integration with corporate payment systems
• Pickup readiness notifications
