Moppi App

Moppi App

Moppi App

Japanese Restaurant App

Japanese Restaurant App

Japanese Restaurant App

Moppi is a Japanese restaurant app designed to elevate the dining experience with convenient features.

Client

Google UX Design Professional Certificate

My role

Visual Design

UI & UX Design

Scope of Work

Interviews, paper and digital wireframing, low and high-fidelity prototyping, usability studies, accessibility, iterating on designs.

Date

June 2024

Project Overview

The problem

Customers often struggle with ordering and picking up food due to language barriers, particularly when waitstaff can't communicate with them. Additionally, those in a rush need a quick and easy pick-up service, while others seek to book a table to work remotely.

The Goal

To design an app that allows users to check the menu, order for delivery or pick up, and have meals brought to their table. The app will also enable customers to skip the line, book tables, and collect bonus points, ensuring a seamless and rewarding dining experience.

User Research

I conducted interviews and created empathy maps to understand users that I’m designing for, their needs and problems. There are 2 user groups that can be identified from interviews.

Identify user needs and pain points

Gain a deep understanding of user expectations and frustrations when using a restaurant app.

Analyze user behaviors and emotions

Uncover the processes, decision-making, and emotional responses users go through when ordering food.

Determine key satisfaction drivers

Explore the features and experiences that are essential for users to feel fully satisfied with the app.

Understand common challenges

Investigate recurring difficulties users face during the ordering process and how the app can address them.

Group 01

  1. Want to see promotions, categories, favourite folder, calories, nutrients, photos of food.

  2. Some of them needs a menu in different language.

  3. Often pick up coffee and food for the office, so they need an app for easy ordering

Group 02

  1. They want to save time on travelling so the restaurant should be nearby.

  2. They want to find information about the level of spiciness of the dish.

  3. Restaurant where they can also work remotely on their computers.

Paint Points

Financial

Difficulty finding affordable option.

Process

Difficulty adding an item to an online shopping cart. Process is not streamline.

Support

Support not easily accessed.



Product

Difficulty reading small text,

lack of nutrients, allergens, and calorie information,

no categories, “favorites” folder, or food delivery tracking, limited language choices, no recommendations or Discounts.

Personas

Personas

Personas

Based on the user groups identified from interviews, I created two personas that represent the common needs of the users. These personas help in understanding key pain points and goals, allowing for more targeted solutions that align with user expectations.

Problem Statements

Alina

Alina

Alina

Alina is a working adult who needs an easy app experience to order and pick-up food and also find restaurant where she can work remotely because she wants to save time and develop her skills.

Leo

Leo

Leo

Leo is a student in Poznań who needs an easy app experience to order food in his native language and navigate the app without language barriers because he doesn’t speak polish and waiters are unable to communicate with him.

User Journey Map

User Journey Map

User Journey Map

Mapping Alina’s user journey revealed how helpful it would be for users to have access to a dedicated Restaurant’ app.

Competitive Audit

Competitive Audit

Competitive Audit

To conduct a competitive study, two sushi restaurants, along with one pizza place and one ice cream shop, were selected to compare the information provided and the overall food ordering experience.

Product Values

By synthesizing user research, key insights were identified, forming the foundation for the Moppi app’s core values. These values shaped tailored value propositions, emphasizing accessibility, flexibility, reliability, and professional solutions to meet user needs seamlessly.

Accessibility

Inclusive and user-friendly, with multi-language support, a simple ordering flow, accessibility features like screen reader compatibility, high-contrast mode, and scalable text size for better readability.

Process

Flexibility by providing personalized suggestions, a variety of payment methods, adaptable delivery options, the ability to save favorites, and remembered order preferences for a seamless experience.

Reliability

Reliability with real-time order tracking, detailed nutrient and allergen information, clear food photos, a rating system, and secure order and payment confirmations.

Proffessional

Is reflected in our transparent discounts, real-time chat support, accurate wait times, and a commitment to no hidden fees.

Storyboard scenario

I created two types of storyboards – big picture to map the overall user journey and close-up to focus on key interactions – ensuring a clear and seamless user experience.

User Flows

I created a user flow to visualize the steps users take, identify potential pain points, and streamline the journey for a smoother, more intuitive experience.


User task: check the menu, order food to the table or use the pick up service, book a table

Site Map

I created a site map to organize the structure of the content, ensuring clear navigation and easy access to key information for users.

Wireframes

I created wireframes to outline the structure and functionality of the design, ensuring a clear and user-focused layout. I started with sketches on paper to quickly explore ideas, then refined them digitally in Figma for better precision and collaboration.

Usability Studies

I conducted two comprehensive rounds of usability studies to ensure the design met user needs. The initial study provided valuable insights that shaped the transition from wireframes to detailed mockups. In the second study, I tested a high-fidelity prototype, identifying areas that required further refinement for an optimal user experience.

Affinity Diagram

After completing the study, I synthesized the data and categorized it to uncover common themes and generate actionable insights. This process utilized the Affinity Diagram methodology, allowing me to organize observations effectively and prioritize key findings for the design.

Insights

Improving Visibility and Access to Information

Users need a more intuitive way to find the opening hours information and better cues for what steps are required to contact support.

Introducing Default and Confirmation Options

Users need a default option “as soon as possible” for the order time and a confirmation page after booking a table.

Facilitating Regular Actions and Orders

Users need a repeated action of booking a table (i.e., once a week) and an easier experience while picking the time for the order.

Simplifying Allergen and Review Visibility

Users need to have the allergens and reviews appearance changed as they are overwhelming.

Clarifying and Enhancing Visual Elements

Users need icons that are not misleading for them and want the number of items displayed in the basket.

Minimizing Disruption During Actions

Users don’t want the pop-up notification while adding an item to favorites.

Improving the First-Time Login Flow

Users want to have the option to swipe the screen while logging in to the app for the first time.

Optimizing User Navigation and Preferences

Users need better options and clarity for navigating the app and completing key actions efficiently.

Design System

I conducted two comprehensive rounds of usability studies to ensure the design met user needs. The initial study provided valuable insights that shaped the transition from wireframes to detailed mockups. In the second study, I tested a high-fidelity prototype, identifying areas that required further refinement for an optimal user experience.

Design System

I conducted two comprehensive rounds of usability studies to ensure the design met user needs. The initial study provided valuable insights that shaped the transition from wireframes to detailed mockups. In the second study, I tested a high-fidelity prototype, identifying areas that required further refinement for an optimal user experience.

Prototypes

Onboarding Flow

Onboarding Flow

Onboarding Flow

This onboarding flow introduces the app's key benefits—flexibility and reliability—before guiding the user to the login screen for a seamless start.

Cart Flow

Cart Flow

Cart Flow

In this flow, the user adds items to the cart and reviews the dish details, including ingredients and customization options. After finalizing the selection, the user proceeds to payment and receives an order confirmation.

Search Flow

In this flow, the user searches for products and selects the 'Sushi' category. After choosing items, the user adjusts the quantity using +/- sliders and refines the selection with additional filters to tailor the order.

Booking a Table Flow

Booking a Table Flow

Booking a Table Flow

In this flow, the user selects the date, time, number of guests, and whether the booking should be recurring. After confirming the details, the user receives a booking confirmation.

About us & Profile Flow

About us & Profile Flow

About us & Profile Flow

In this flow, the user accesses the 'Info' section to find detailed information about the restaurant.

Search Flow

In this flow, the user searches for products and selects the 'Sushi' category. After choosing items, the user adjusts the quantity using +/- sliders and refines the selection with additional filters to tailor the order.

Search Flow

In this flow, the user searches for products and selects the 'Sushi' category. After choosing items, the user adjusts the quantity using +/- sliders and refines the selection with additional filters to tailor the order.

Outcomes

Because this was a conceptual project, I didn’t have access to real usage data.

However, I defined success metrics that would be used in a real-world release:

• Time to complete an ordering flow reduced by ~25%

• Task success rate > 90% on first attempt

• SUS score aiming for 80+

• Fewer errors during booking and ordering


I learned the value of early testing, the importance of simplifying complex hardware interactions, and how defining constraints helps drive clearer design decisions.


Next iterations

I would further develop error states, improve accessibility, optimize cross-device layouts, and refine notification behavior based on user feedback.

Outcomes

Because this was a conceptual project, I didn’t have access to real usage data.

However, I defined success metrics that would be used in a real-world release:

• Time to complete an ordering flow reduced by ~25%

• Task success rate > 90% on first attempt

• SUS score aiming for 80+

• Fewer errors during booking and ordering


I learned the value of early testing, the importance of simplifying complex hardware interactions, and how defining constraints helps drive clearer design decisions.


Next iterations

I would further develop error states, improve accessibility, optimize cross-device layouts, and refine notification behavior based on user feedback.

Outcomes

Because this was a conceptual project, I didn’t have access to real usage data.

However, I defined success metrics that would be used in a real-world release:

• Time to complete an ordering flow reduced by ~25%

• Task success rate > 90% on first attempt

• SUS score aiming for 80+

• Fewer errors during booking and ordering


I learned the value of early testing, the importance of simplifying complex hardware interactions, and how defining constraints helps drive clearer design decisions.


Next iterations

I would further develop error states, improve accessibility, optimize cross-device layouts, and refine notification behavior based on user feedback.

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