Overview
Impacts
80% improvement in staff satisfaction, as reported by front-of-house teams who no longer felt overwhelmed by constant phone interruptions
~0 missed calls, ensuring every caller reaches the assistant
~20% average increase in captured daily phone orders
70% increase in customer satisfaction ratings due to faster and more accurate ordering experience
Problems
Independent and small-to-medium-sized restaurants heavily rely on phone orders, yet struggle to handle calls efficiently due to limited staff and busy service hours. This frequently leads to:
Significant missed revenue from unanswered phone calls
Inconsistent and frustrating customer experiences
Labor-intensive manual logging of orders and reservations
Lack of visibility into missed business opportunities
Market analysis revealed approximately 35% of customers still prefer ordering by phone, emphasizing the ongoing importance of an effective phone-order solution. Despite increasing digital options, phone orders remain critical, yet an effective turnkey solution did not exist.
Users
Rachel
Host
Works the front counter at a popular takeout spot. Between packing orders, ringing up customers, and answering questions, she juggles a lot at once. The phone rings constantly, and she does her best to catch it between tasks.
Gets overwhelmed when multiple calls come in while she’s helping someone in person. Has no system for tracking what’s been said or promised over the phone. Just wants a tool that takes care of routine calls so she can focus on the guests in front of her.
Marco
Restaurant Manager
Runs a fast-paced Thai restaurant in Atlanta. During service, he's constantly on the move, checking on the kitchen, greeting customers, and managing staff. He knows every missed call could be a lost order, but during peak hours, it’s impossible to catch every ring.
Keeps his phone nearby but can’t answer every time. Gets frustrated with missed calls, double bookings, and no record of what happened. Wants fewer interruptions and a way to reliably capture every call without hiring more people.
David
Customer
Calls his favorite restaurants a few times a week to place orders. He prefers the phone, wants to ask questions, hear the tone, confirm everything. But too often, no one picks up or he’s stuck on hold with no idea if his order went through.
Hates being ignored or misunderstood. Gets frustrated when he has to repeat his order or when the food comes out wrong. Just wants a quick, clear, and reliable experience every time he calls.
My Role
As the sole product owner and designer, I employed a detailed, structured, and iterative design process, systematically integrating user feedback and data-driven insights at every stage
Initial Sketching & Flow Mapping
I began by creating initial sketches and detailed user flow diagrams to clearly visualize core functionalities, interactions, and user journeys, ensuring alignment with identified user needs and business objectives.
I sketched the flows and components to guide AI in creating a proof-of-concept prototype.
I sketched the pages to guide AI in creating a proof-of-concept prototype.
POC Prototyping
Rapidly developed a proof-of-concept prototype using Lovable to validate initial assumptions about usability and functionality.
Conducted preliminary tests with restaurant staff and operators to capture qualitative feedback and insights.
A proof-of-concept prototype using Lovable to validate initial assumptions about usability and functionality
Early User Feedback
Engaged directly with users to collect qualitative insights and identify key usability concerns. User feedback revealed specific areas for enhancement, such as call clarity, order accuracy, and streamlined payment processes.
83% of users described the AI voice as “natural and easy to understand,” boosting trust during calls.
Some customers reported confusion when receiving payment links without hearing a clear verbal confirmation.
Restaurant staff felt unsure whether an order had been fully processed due to lack of real-time confirmation alerts.
Drag-and-drop was well received, but 3 out of 5 staff preferred an additional button to quickly advance orders during peak hours.
High-Fidelity UI Design
Translated user feedback and initial test data into comprehensive, high-fidelity UI designs using Figma, addressing key pain points and optimizing the overall user experience with clear and intuitive interfaces.
Usability Testing
I conducted structured usability testing with 5 diverse restaurant partners to evaluate design effectiveness in real service environments. Across four iterative rounds, I refined Callo’s experience using both quantitative metrics, such as task completion rates, error frequency, and satisfaction scores, and qualitative user feedback from frontline staff and managers.
Round 1 (Initial Prototype)
Validated the AI assistant’s call handling and conversation structure. While users appreciated the clear voice and polite tone, they flagged moments of hesitation and misrecognition. This round established baseline performance and exposed early friction points in the voice UX. Despite limitations, 3 restaurants successfully captured at least one previously missed order per shift.
Round 2 (Payment UX)
Most restaurants traditionally don’t collect payment for phone orders, which often leads to revenue loss when customers fail to pick up their orders. Staff also noted discomfort from customers when asked to share card details over the phone.
To solve this, I introduced an automated SMS payment link feature. After testing different timing and phrasing strategies, I redesigned the confirmation flow to feel more secure and effortless. This led to a 28% increase in payment completion and significantly reduced unclaimed order incidents, while also making customers feel safer and more in control.
Round 3 (Order Management Usability)
Tested and refined the Kanban-style order management. Staff found it easier to track call outcomes, move orders through the pipeline, and understand customer intent. Completion time for logging and acting on a new order dropped by an average of 43%.
Round 4 (Advanced Functionalities)
Restaurant staff emphasized the need for accurate, real-time information to be relayed by the AI assistant. However, most existing systems required manual syncing or lacked clear controls.
To address this, I focused on improving the restaurant settings experience, specifically business hours, seat limits, and the menu builder. By making this touchpoint intuitive and flexible, restaurant teams could easily update critical info like item availability or holiday closures, enabling the AI to respond accurately in real time. After refinement and testing, 100% of partner restaurants reported feeling confident that the AI reflected their current operations, leading to fewer mistakes and better customer trust.
Solutions
Following multiple rounds of design, testing, and iteration, Callo emerged as a powerful yet intuitive voice assistant platform purpose-built for restaurants. It automates the most time-consuming and error-prone aspects of phone communication, taking orders, handling reservations, collecting payments, and logging interactions, so staff can focus on delivering great service in person. The product includes:
A natural-sounding AI voice assistant trained specifically for restaurant conversations
Ensures every call is answered promptly and professionally, reducing staff interruptions and lost orders.
Solution
Real-time order and reservation capture, with customer intent recognition
Accurately understands and logs what customers need, whether it’s placing an order or booking a table, so staff don’t have to.
Solution
SMS-based payment collection to reduce no-shows and increase reliability
Lets customers securely pay from their phones, helping restaurants avoid unpaid or abandoned orders.
Solution
A clean, Kanban-style order management and reservations calendar for easy tracking and fulfillment
Gives staff and managers a clear, at-a-glance view of every active order and upcoming reservation.
Solution
Built-in analytics to surface peak hours, popular items, and missed opportunities
Helps owners make smarter decisions about staffing, menu focus, and hours by turning conversations into actionable insights.
Impacts
80% improvement in staff satisfaction, as reported by front-of-house teams who no longer felt overwhelmed by constant phone interruptions
~0 missed calls, ensuring every caller reaches the assistant
~20% average increase in captured daily phone orders
70% increase in customer satisfaction ratings due to faster and more accurate ordering experience
Reflection
Callo exemplifies strategic, user-centric product design, showcasing:
Clear resolution of genuine industry pain points
Effective use of cutting-edge technologies for rapid and impactful solutions
Empathy-driven design focused on real-world usability and measurable business impact
As a product founder, designer, and builder, I am committed to continuous evolution, enhancing Callo’s capabilities to sustain positive impacts in restaurant operations.
Project information
Year
2025
Services
0-1
SaaS
UX, Visual & Interaction Design
More work
