Tum-Me : An app that helps you find good food on great deals wherever you are!

My first UX project at General Assembly

I was paired up with my classmate Alex for this project and he chose Food. A topic that comes up every day in our lives. Where to eat and what to eat?

Step 1: User Research

The common topics surrounding food.

Questions for my interviewees on the applications they would use to search for food and listed my questions as

  • What do you do when it’s time to pick a place to eat?
  • What is the daily routine like?
  • What is the reason for not using a app?
  • What kind of app drives you to download?
  • What is the deciding factor to use the app?
  • How does the app benefit you?
  • Are there discussions with your friends or colleagues about the place to eat?
  • What are some of the daily challenges you face making a decision?
  • Which is the best function on the app that you are currently using?
  • How long do you spend searching for food of your choice?
  • What is the allocate budget for meals?
Interviewing fellow students

Summary of my findings

From the 5 interviews I gathered that many of us will allocate a different budget according to occasions. Location is the main factor when making a decision as most will not travel for food except for weekends. All users would welcome an app that shows promotions or discounts. It came as a surprise when only 1 person mentioned that she will look at the reviews. Many of them are happy to try out new restaurants.

With the data gathered, I started my next step to Affinity Mapping.

Step 2: Synthesising

I wrote down the main points that I have gathered from the interviews on post-its according to their Pains, Pleasures, Context (Where & When) and Behaviour. I was trying to get the Problem Statement out by highlighting their “I” Point Of Views.

“I” statements from the users’ points of view

It was not easy to synthesize and find the essence in my data. I realised that I should have set my questions to be more open ended. When I played my audio recordings of the interviews, I was also caught trying to influence my interviewees by prompting answers. So this could be the reason why I had difficulty in finding the essence of my research.

When I group the data collected, it was clearer that I had to solve the problem based on context, i.e. Where and When. The Pains from the users were mainly not being able to decide on where to eat. Their Pleasures are mainly derived from the discounts they find. However, all users mentioned that they will look for food based on the location and time of meals. Out of the 4 users I interviewed, only 2 of them use an app actively to search for restaurants with discounts. The other 2 who do not use an app gave the reason that they do not have an incentive to do so.

I then started to look at the app frequently used by my interviewees.

Reviewing the steps the users have to take using their current app

Step 3: User Flow and System Flow

Problem Statement

Even with many “food guide” apps available, users are not 100% satisfied with the ones they are using. Even for the non-users, they want a fuss-free search engine that is reliable and relevant.

I started to list out the user flow, beginning from the time they have to choose a place for their meals. I went through the process with my users and got a better idea on the flow of their decision making process. This allows me to understand their purchasing behaviour better.

From the user flow, I then started to note down the flow of the system. During this process, I had to keep in mind that I have to solve the problem of an app being overloaded with too much information. Therefore I started mine off with the filter process.

Solution Statement

To create a simple app that will show users substantial amount of discounts offered by restaurants, and has the function to share the restaurant they have found. Create a simplified version of a food app.

Step 4: Prototyping

As I was sketching the details I need to include in the app, I referred to the system flow to ensure that I had the steps listed in the same way.

Once I had my basic sketch on the features, I went back to my interviewees to get their feedback on how I can improve on the functions. I did not expect to face dilemmas in deciding the flow of the system. I had to decide on what are the key essentials of the app since I wanted to minimise unnecessary steps and information.

Homepage for Login or Sign Up

From the interviews, I narrowed down to these 4 pieces of information that were more significant in helping them make the decisions. They are Location, Cuisine, Budget and Discounts.

Results list

From the interviews, I also gathered that users find it useful to have the ability to share their reservation. Thus I included this function in all the result pages and the Thank You page.

Making reservation and finally a Thank You page to allow users to share their reservations

For Continuity

  1. I would need to include “number of pax” on the filter page, as this will affect the results shown for those restaurants with promotion for big groups or minimum number of guests.
  2. The category of cuisine should be shown on the top of each results page so users are able to identify the types of places they want to go more easily.
  3. There should be incentive for users to download the app and sign up. This can be done through special discounts for members only, or rewards for users who frequently use the app.

Reflections

  1. Although I enjoyed the process of research but I realised that I did not spend enough time on this. I could have asked more questions relating to users’ behaviour as I encountered difficulties when I tried to collate their information into groups.
  2. I should have taken more pictures with my users and interview notes, that will show the process of my research and how I derived my findings.
  3. All in all, it was a great learning journey as I have a clearer direction on where I should put more emphasis on when collecting user data.

Thank you for reading!

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