Pizza Inn Application
My objective for Weeks 3–5 was to put together a presentation on a business of my choosing. I started by considering a wide range of potential themes before settling on one. I interviewed people to find difficulties with food delivery applications, segmented the market so that a pizza delivery app could reach its ideal users, and solved any possible app issues that I found in the process of my study. I provided design options that were pleasant to users and discussed their benefits. In the last round of this procedure, I highlighted the unique features that set my software apart from the competition.
The overall background story of Pizza Inn
PizzaInn is a popular Mauritius-based pizza chain known for its gourmet pies and its use of creative, locally inspired toppings and sauces. It was founded in 1958 by two brothers from Texas with an eye towards becoming national. Pizza Inn’s distinctive pizzas were very popular between 2018 and 2021, prompting the company to open several locations around Mauritius. However, customers had a lot of problems with the pizza delivery app.
Primary Goal: To facilitate the end-user using an app that allows users to not only order pizza but also make the app easy to navigate and user-friendly.
My role
My role in this project required me to create a mobile app prototype for Pizza Inn with the end objective of enhancing the app’s usability. Many customers had difficulties with the previously accessible app; hence, this redesign puts extra effort into refining the pizza customization process, improving navigation, and shortening the time it takes to complete a transaction. Its objective is to make buying pizza from Pizza Inn easier and faster by giving customers a streamlined way to browse the menu, place orders, and specify their preferred toppings. Customers will enjoy a positive and problem-free app experience because of this.
Design Problem
I had to do some research on the problem that people faced when ordering from a pizza app. After analysing each problem that the current app had,
came to the following conclusions:
After finding each of the following design problems, I started to do research on the target audience
Since people of the baby boomer generation, Generation X, Generation Y, and the Z generation are the most likely to use a pizza delivery app, they were my primary focus. I targeted pizza lovers who were also able to utilise the app in my market analysis. In my procedure documentation, I portrayed three different people: a former army officer in his sixties, a high school senior, and a middle-aged bookstore. From what I could see, they were the ideal target audiences for a pizza delivery app.
After the target audience came, I chose three different age groups who love eating pizza.
Design Solution
I then had to think about how I could make my application stand out from the crowd and this is what I came up with
key research moments and insights
Case studies of Domino’s Pizza, Pizza Hut, and Debonairs Pizza helped me learn valuable lessons, such as how to recognise problems with apps, evaluate the benefits and drawbacks of current apps, and come up with strategies to solve problems users have while placing orders. I was able to solve difficulties with current apps and come up with unique features like AI algorithms thanks to my study. An artificial intelligence recommendation system that provides individual pizza options along with calorie counts is an innovative and user-friendly addition to the pizza delivery app
Case Study 1
Domino’s Pizza
Case study 2
Pizza Hut
Cast study 3
Debonairs Pizza
When finishing with the study case, I had to do the Ideation for each of the frames
Weeks 6–8 were dedicated to finishing the project report. I created a survey with eight questions and collected data from a sample of people in general. I studied the colour schemes and identified issues with existing apps like Domino’s Pizza and Pizza Hut’s mobile offerings. Five different ideas for my Pizza Inn delivery app were then created, each with a full set of wireframes for six screens. I created a low-fidelity wireframe beginning with the sign-in and sign-up frames and ending with the payment frame, outlining the user flow and colour palettes along the way. Peer review was used to make the design even better.
When finished the ideation, then came the user flow, where I had to show each of the different screens
Logo remake
In the logo remake section, I want to remake the logo as it was poorly done and all the typography that they used didn’t match the logo.
I then started to add colour to the new logo.
As it was an Italian pizza restaurant and the original logo was red, white, and green, I want my logo to remain in the same colour palette.
Low Wireframe
The low wireframe was the next part of my process of creating the prototype. Here I asked for feedback, and I made changes to the prototype.
Final logo
when finally finished choosing my final logo, I made the icon for the application
And last, I did the icons for the application. Each of the icons that I designed was specified for the application, from the profile icon to the exit icon.
In the last four weeks of the project, I built a prototype of the High Fidelity application’s framework. The whole process, from registration to payment, has to run smoothly. Then I did some user testing, recording random people using the prototype and collecting their thoughts on camera. After receiving helpful feedback, I modified the prototype and posted the Figma link with a comprehensive blog outlining the project’s background, methods, and results.
Challenges and Successes
After finishing the Figma prototype and connecting all the buttons to their corresponding frames, I showed it to my peers to get their thoughts. Together, they were able to make the required changes and modifications to the design.
Explaining each frame
Figma prototype link:
YouTube prototype link:
The time I spent working on the PizzaInn app was well spent. I saw firsthand how a pizza delivery company established in Texas was able to successfully adapt to the Mauritian market. It was a satisfying task to create a better prototype of a mobile app. It was crucial that the app be adapted to meet the demands of users of all ages, from baby boomers to millennials and beyond. One notable use of AI is in tailoring pizza recommendations and nutritional information to the individual. Our iterative approach was directed by user input, resulting in a user-friendly, aesthetically pleasing, and effective app that improves upon the PizzaInn experience.
The project recognizes Pizza Inn’s transformation from a Texan restaurant to a successful Mauritian business known for its culinary adaptation. I wanted to ease pizza personalization, navigation, and ordering by improving the mobile app. I wanted Pizza Inn’s different customers to find it easier, more fun, and more efficient. Using AI algorithms for pizza selections and calorie counts addressed generational preferences. My software was visually appealing, user-friendly, and customizable thanks to user feedback and modifications. PizzaInn values local flavours and customer service; therefore, this approach matches
PizzaInn’s transformation from a 1958 Texas startup to a Mauritian pizza success showed its versatility. Improving the app, adding AI for personalised pizza selections, and taking user input were crucial. My project was to create a user-friendly, attractive, and efficient application that reflects PizzaInn’s local flavours. This project improved customer service and demonstrated food delivery service capability.