A meal customization and delivery mobile application that centralizes dietary preferences and restrictions.
Personal Project
Jump to High-Fidelity PrototypeUser Research, UI/UX Design, Interaction Design, Visual Design, Wireframing, Prototyping, Branding
July 2021 - September 2021
Revamped in December 2022
Figma, Adobe Illustrator + Photoshop, Miro
By following a design thinking approach (non-linear and iterative), I was able to focus on the most essential aspects for users. The process fostered truly understanding users, bypassing assumptions, reconsidering problems, and developing creative solutions to prototype and test.
My experiences and conversations with those in my immediate network provided an initial basis for the problem space. But, to really understand the area and learn about users' interests, motivations, frustrations, and pains when ordering and customizing food, I spoke to more people formally.
I collected key insights after analyzing each interview using empathy maps. The conversations validated my initial assumptions and also added to my knowledge of the problem space.
Essentially, the interviews highlighted several pain points that users experience when they order custom meals from restaurants.
Preliminary market research clarified that Freshii and Subway are Mealize's top direct competitors: they both provide reasonable healthy, customizable meals that can be delivered to their customers. Additionally, Pizza Pizza is an indirect competitor that offers customizable meals but operates within the market's more indulgent / less healthy space.
I aimed to learn more about how competitors are helping users customize meals by comparing the user experience of each competitor's mobile application as a new and returning user.
To keep my decisions moving forward user-centered, I formed a representative user persona that clearly portrays Mealize's users. Jasmine is the primary persona, and they were created by compiling the learnings and patterns from the empathy maps.
I analyzed the steps a user like Jasmine currently takes to attain a meal that meets their requirements. Alongside this, I mapped out the flow of emotions and opportunities for a potential solution to their problem.
I now had a better understanding of the context in which users would use the application and their feelings when completing those possible tasks, so I created a user flow diagram that clearly describes the actions a user would take on the app.
To get the creativity going, I brainstormed ways to combat user frustrations with customizing and ordering meals using the Crazy Eights exercise.
My minute-long sketches led to some interesting concepts I could build on to develop more specific features and screens for the food app.
Based on all the research conducted thus far and an initial ideation session, I had a few top ideas to implement in my food app.
I drew out several screens for the main user flow based on the initial ideas and progressively developed them to formulate a meaningful user flow that achieves the critical task.
I had an indication of how the interactions within the application would work. But, at this stage, it was essential to emulate the interactions between different elements on the screens so that users could achieve their end goal: a delivery for a customized meal of their choice.
I used index cards to make a paper prototype that included screens essential to completing the main user flow: a returning user customizing and ordering a menu item for delivery.
I spoke with some potential users and conducted a lean evaluation of my current, envisioned design. The conversations confirmed that the app would help order meals that meet their needs. However, participants noted that while a rewards system be interesting, there are other features they believe would directly enhance the customization experience. Therefore, I dropped this feature, concentrating on aspects that would enrich the user experience, specifically for meal customization.
I created a digital (mid-fidelity) prototype on Figma with the feedback. The following are two fundamental screens:
After developing a working, mid-fidelity prototype, I wanted to investigate its effectiveness with real users. I conducted a formal usability study with five participants, asking them to complete specific critical tasks and answer some vital questions to help improve the design in a user-centered way.
I organized each observation from the usability study into an affinity map to understand the sentiments toward the user experience of customizing and ordering food on the app.
To further synthesize the information collated, I highlighted the key themes and formed encompassing insights to improve the user experience.
The usability study highlighted an essential weakness of the current design: customization and user preferences were not at the forefront. The primary revision involved ensuring the dietary requirements page was more central in the user flow - right at the start for new users and easily accessible throughout multiple areas. This way, users can more easily navigate the app and hasten the customization process.ext
As I created a high-fidelity prototype, I continued to make more design revisions grounded in the insights from the usability study.
After iterating through numerous related concepts to Mealize's brand, including its association with customization, health, freshness, and food, I decided to focus on a plate and a paintbrush for the logo's pictorial mark. The icon style incorporated a simple dish to reflect meals and a paintbrush to echo personalization. The artistic style included a leaf-like brush, identifying the connection with fresh and healthy food. I designed the logo in Adobe Illustrator, using the Golden Rule approach for the pictorial component.
I also established the brand’s typeface, colour palette, and logo variations that would be consistently propelled throughout the mobile application interface.
Everything I learned from the research, ideation, and testing stages went into the high-fidelity prototype. It depicts the interactions, visual design, and overall function of the intended food customization app.
These four essential features directly address the central problem statement of young professionals struggling to find and order meals that meet their specific dietary needs, preferences, and restrictions, providing a seamless and customized solution that eliminates frustration and uncertainty.
Personalized Dietary Profile
Mealize records the user's diet, allergies, intolerance, and flavor preferences on setup. This information informs the meal suggestions and food customization options to ensure the app is completely tailored to the user's food habits, offering effortless and efficient meal customization.
Priority Ingredient Filter
The app categorizes, filters, and prioritizes ingredients based on the user's unique dietary requirements and preferences, streamlining the customization process and eliminating the need for time-consuming searches for ingredients. Moreover, it allows users to fine-tune their orders by adjusting the precise proportion of each ingredient - a completely personalized experience.
Recommendation & Reorder Assistant
This feature enhances user convenience and satisfaction by providing tailored recommendations based on their past orders and allowing for quick and easy reordering.
Quick & Easy Checkout
This feature improves the user experience by simplifying the checkout process, facilitating faster and more efficient order placement.
The Mealize project was enjoyable and informative for me. It was an excellent chance to enhance the food ordering experience that I was very familiar with but in a domain I was unaware of. Though I order food through various apps regularly, I do not have any allergies or intolerance I need to account for. I developed an appreciation for the daily struggle of easily, efficiently, and reliably ordering meals from platforms that lack customization capabilities. Going through the research process, ideation stages, wireframing, prototyping, branding, testing, and so much more was an insightful experience. It taught me a lot about this problem space.