Airo Global Software

Think Beyond Future !

Case Study: Food Delivery App

- Posted in App Development by


Foodiday is a food delivery application that provides food delivery at your doorstep in very little time and with the best packaging and hygiene. By providing the food from every famous food place nearby online food ordering is the process of ordering food from an application. The product can be either ready-to-eat food. This online food ordering system sets up a food menu online and customers can easily track the orders. There are various facilities provided so that the users of the system will get service effectively. Increasing the use of smartphones is also considered as a motivation. So that any users of this system get all services with a single click. Another motivation can be considered as the system will be designed to avoid users making fatal errors, users can track their food items through GPS users can provide feedback and recommendations and can give ratings, It will give appropriate feedback to restaurants. In the proposed system there will be no limitation on the number of orders the customer wants.


With the development of Foodiday.We know that people look over the mobile app for ordering food to comfort their life. With the huge number of young professionals in the big cities, people can’t find much time to prepare food. By developing this food delivery app to make the job too easy in Kerala. Download this app from the play or app store, register into the app, select the menu to place food delivered to your doorstep. Most of the young professionals and other office goers found this method too easy to place a food delivery app in Kerala and has become in stand popular among users. People have a huge number of choices to select among the apps to compare and pay with offer price from online food ordering apps.

Foodiday is a food delivery app designed to make it simple to find and order food one is craving.

The time frame for developing a food delivery app:

  • While using flutter:16 weeks
  • While using Native-Android:16 weeks
  • While using Native-IOS:16 weeks

Below are some of the issues that we wanted the redesign to address.

The community of existing food delivery apps causes it hard to find dishes one wants.

  • Grouping dishes by eatery forces users to scroll through long restaurant menus
  • Many dishes have no pictures making it so effort to scan and know what they are ordering

Current explanations do not sufficiently address those with dietary restrictions

  • There are no options to ban foods with certain ingredients
  • User has to read dish explanations or avoid ordering from certain restaurants

Suggested restaurants and dishes are not personalized

  • No option to count dish or restaurant to favourites
  • Easy to reorder past dishes, but falls short of suggesting similar ones

The interface offers too many food options

  • Many customers who use the service are usually hungry, busy, or tired and needs instant-gratification
  • Do not require making too many decisions
  • Lower patience levels
  • Want things very quick

My Role

  • Do competitive study by trying contender apps and reading app reviews
  • Make user interviews with students and instructors who order food online or eat out
  • Develop and post user surveys online
  • Participate in generating user personas


Domain Research

With the project idea expressed, the team identified the iOS App Store for food delivery apps. This gave us a better sense of the current food delivery apps out there. For each app, we determined what key elements they had and read reviews to determine pain points and what features people like. We used this data to formulate our user interview questions and will review them when making workflow and design decisions.

Below are some concepts collected from user reviews:

  • Need choice to cancel the order
  • Need right notification of delivery will be late
  • Notification if the dish is unavailable and suggests another
  • Advise customer if ordering near restaurant closing time
  • Option to include a dish to favourites for easy reordering
  • See order status and delivery ETA on the home screen
  • display contact info of deliverer and restaurant
  • display order number with client support phone number

User Interviews

My team reached around interviewing students and instructors to know about the following:

  • How often, why, when, and how they order food online
  • Why they would select one food delivery service over another
  • Their background using one of the food delivery services
  • How food allergies affect their placement experience
  • How they locate new restaurants and dishes
  • How they order food in the app
  • Areas they consider competitors can enhance on

As I had never ordered food online before, conducting user interviews gave me a better sense of what users run through in the ordering and delivery knowledge by responding to the 5 W’s (who, what, where, when, why, and how). It was also useful in coming up with more questions as unexpected points were introduced.

From the user interviews, we found that customers are:

  • Food-based or restaurant-based
  • Price susceptible and are concerned about delivery fees
  • Enjoying more correct order status information
  • Visually driven.
  • Neutral in helping local businesses and organics

User Surveys

Afterwards, we developed and deployed a user survey on different communities on Reddit which garnered 315 answers over 3 days. The survey was one of the key ways of deciding what elements are required and not with more significant confidence. It also ensures some of the user interview results.

The survey results also modified the initial project idea, which was a “Don’t make me think” technique to food ordering with customized proposals, rating, scheduling, and budgeting.

We discarded the scheduling and budgeting features as most people are not curious about scheduled deliveries and people order food a lot further from the app, making budgeting unusable.


With the research piece concluded, we drove onto the planning stage where we developed user personas, customer journey maps and user flow diagrams.

User Personas

From the user interview conclusions, we made 2 user personas, restaurant-based and food-based users. Restaurant-based users track the current model of food delivery apps where dishes are grouped by the restaurant. Food-based users follow a new model where they are more curious about finding dishes rather than restaurants.


  • Need to visit the eatery first before ordering online
  • Need to read restaurant reviews and blog mentions
  • Usually, order from the usual restaurants
  • Will utilize whatever food delivery app the restaurant endorses


  • Enquire for food to satisfy one’s cravings.
  • Look at pictures to comprehend what to expect
  • Periodically tries ordering from new restaurants


  • Don’t need to or couldn’t cook or pick up food
  • Deals price, restaurant type, delivery fees, and speed are the most
  • Looks at a distance, thoughts, pictures, and values when selecting a restaurant

Customer Journey Map

Afterwards, we made a current and prospective customer journey map to emphasize the touchpoints, actions, thoughts, and pain points. To help us know the current flow, we downloaded the foodiday mobile app and executed through methods to see how the apps completed or did not meet the user’s requirements.

User stories

Here are the user narratives showing the user’s plans for each major page.

Dishes page

  • As a restaurant-based user, I need to identify restaurants so I can call from my favourite restaurants
  • As a restaurant-based user, I enjoy discovering the best restaurants for a typical cuisine in my area so I can order delicious food
  • As a food-based user, I like to search for distinct dishes so I can see food I am craving for
  • As a user, I like to see presented dishes founded on my choices so I do not have to create as many decisions
  • As a user, I like to discover dishes with free delivery or other values so I can save money
  • As a user, I like to see my famous dishes so I can reorder them

Filter page

  • As a user, I like to sort dishes by distance, rating, cost, and favour so I can uncover dishes fast
  • As a user, I like to filter dishes by cuisine or allergies so the recommendations fit my tastes and dietary limitations

Dish info page

  • As a food-based user, I like to see pictures of words so I have an idea of what I am calling
  • As a user, I like to know which restaurant a dish comes from so I can create reported purchasing decisions
  • As a user, I like to check restaurant reviews before summoning so I can be guaranteed the food quality
  • As a user, I like to know the restaurant beginning hours so I understand when they can deliver
  • As a user, I like to count dishes to my favorites so I can readily revisit and/or reorder them
  • As a user, I like to be capable to convey a link to the dish to others so I can bring others to check it out
  • As a user, I want to customize dish toppings so the dish fits my tastes
  • As a user, I like to count a note to a dish so I can select element changes or omissions

Cart/Checkout page

  • As a user, I like to understand the estimated total before fitting out so I know how much I will be paying before I input the lesson and payment facts
  • As a user, I like to be able to go back to scanning so I can count more dishes to the cart
  • As a user, I like to change the dish options or remove dishes in case I switch my mind
  • As a user, I like to have my address and payment points saved so I can fit out faster
  • As a user, I like to be capable to count delivery instructions so the delivery agent can buzz themselves in
  • As a user, I want to have the opportunity to have the pass emailed to me so I can get job reimbursements

Order status page

  • As a user, I like to have the accurate GPS tracking of my order so I understand when it will arrive
  • As a user, I like to be able to call the client consent or the delivery agent so I can track up if something goes wrong
  • As a user, I like to be capable to cancel an order if I made a misstep
  • As a user, I like to order the food and delivery service individually so my rating is more precise
  • As a user, I like to pay the delivery tip after the delivery so I can tip according to the delivery rate
  • As a user, I like to see tickets of past orders so I have a record if the order that reaches is incorrect


For this project, the group determined to try a hybrid approach to prototyping where rather than making the mockups from scratch for each set of fidelity, we repeated them. This will permit more time for testing and fixing the prototype. Extra time was also given to understanding how to build a high-fidelity prototype with spirits in Invision Studio.

E-mail id: [email protected]

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Author - Johnson Augustine
Chief Technical Director and Programmer
Founder: Airo Global Software Inc