Case Study
Dish Dash
Creating a seamless food delivery experience powered by personalization and smart technology.
Background
Prompt
Dish Dash was created to redefine the convenience and personalization of ordering meals. Designed with features like instant reordering of past favorites, collaborative group ordering, and an AI voice assistant, the app ensures a faster, smarter, and more social food ordering experience.
Imagine opening a food app that remembers your last order, helps you and your friends place a single group order effortlessly, and lets you order your next meal with just your voice.
Design Thinking Process
I primarily followed the Design Thinking process throughout this project.
A user-centered approach guided each phase, Empathizing with the users, discovering their frustrations, Defining the problem and their core needs, Ideating thoughtful solutions, and Prototyping, designing and delivering a seamless food ordering experience.
empathize
User Interviews
To understand user pain points, behavior and needs, I conducted interviews and distributed online surveys to users aged 18–45. Participants included students, busy professionals, and families.
The open-ended questions explored their food ordering habits, frustrations with existing delivery platforms, and features they wished existed.
User Personas
Based on user interview insights, I developed three primary personas to represent the key goals, behaviors, and pain points of our target users.
The interviews revealed distinct mindsets and patterns around food ordering, which were synthesized into three unique personas. Each persona embodies a specific set of needs and challenges, helping guide design decisions, prioritize essential features, and ensure the experience feels relevant and intuitive across a variety of food ordering scenarios.
The interviews revealed distinct mindsets and patterns around food ordering, which were synthesized into three unique personas. Each persona embodies a specific set of needs and challenges, helping guide design decisions, prioritize essential features, and ensure the experience feels relevant and intuitive across a variety of food ordering scenarios.
Empathy Map
Based on user interviews and persona development, an aggregated empathy map was created to visualize shared experiences, emotions, and pain points. Standout quotes revealed expectations, frustrations, and behaviors that shaped how users think, feel, and act while ordering food. Mapping these patterns provided deeper insight into user needs and helped translate them into meaningful design opportunities.
define
Problem Statement
Despite the rise of food delivery platforms, users still face friction in reordering favorite meals, coordinating group orders, and placing orders in hands-free situations. which led to my design questions:
"How might we simplify and personalize the food ordering process to better fit users’ lifestyles, making it more social, accessible, and efficient?"
prototype
User Flow
Based on the insights gathered, I mapped out a user flow that emphasizes ease, speed, and flexibility from onboarding to ordering, group collaboration, and checkout. The focus was on minimizing steps and offering multiple input methods (tap, type, voice).
Low Fidelity Prototypes
With a clear flow in place, I developed low-fidelity wireframes that focused on core functionality: reorder, group order creation, and voice input. These helped test and iterate the concept and navigation logic early in the process.
High Fidelity Prototypes
Building on feedback and testing, I created high-fidelity prototypes that brought the interface to life with visual polish and interactivity. This final prototype integrates user feedback, real-time elements, and intuitive controls to deliver a complete, accessible and modern food ordering experience.
