Restaurant recommendations for travelers with dietary restrictions.


Interaction Designer
Visual Designer


Aug. 2019 -
Dec. 2019


Research + Inteviewing
Hi-Fidelity Prototyping
Iterative Design


Wireframing Prototype


Being unfamiliar with traveling to a new area usually leads to extensive, exhausting and time-consuming research about places to eat. People with dietary restrictions are anxious while eating out and remain drawn towards restaurants and dishes that they are already familiar with while on the go.


How might we empower travelers with food allergies to venture outside their comfort zone and streamline the information-gathering process for exploring new dining options?

Would Recommend is a mobile app for discovering dining options tailored to people with dietary restrictions using an online crowdsourcing community.


As my first UX design project, I had to take on a versatile role of both a researcher and a designer. As the sole designer on this project, I was tasked with both designing the first few iterations while also recording feedback on those designs.

Afterwards, I realized that participating in the feedback sessions actually provided valuable insight that helped me improve my concepts and hear issues directly from the users themselves.


As a team, we reached out to interview those with dietary restrictions using an online Qualtrics survey, interviews, and a contextual inquiry. These responses were then compiled into an Affinity Map.


A Qualtrics survey was created to identify common food allergies and the frequency of going out to eat.

We learned that food allergies are very common. 9 out of 10 responders said they ate out less than three times per week.


In seven 30 minute interview sessions, we wanted to uncover pain points and points of anxiety in the dining out process.

We learned that people with dietary restrictions juggle a variety of sources to make decisions about where to eat. These sources range from websites to word of mouth.


We observed the end-to-end dining out experience of four users and the tools and strategies used while eating out.

People can narrow cuisines down by key ingredient, most tend to veer towards familiar restaurants. Also, dining with others causes anxiety.


We explored three different designs before settling on a mobile app, as the most practical. Alternative designs were deemed less practical when presented to users.


A large digital display placed at the entrance to dining venues where users can indicate their food allergies and cuisine preferences by touching the screen.

The display then presents a list of dining options in that venue.

Smart screens near eateries provide localized suggestions, but they have limited geographic areas where users would have to find them.


A pair of augmented reality smart glasses that can look at physical buildings. Users drop pins on top of venues that accommodate their preferences.

Inside the restaurant, users can view menu items and ingredients at the table.

Wearables are less feasible but more novel, with fewer features.


This app lets users look up food options and check recommended selections based on allergies and preference on a personalized profile.

Users tend to have phones handy, so a mobile app is easily integrated into user lifestyles.

Taking into account the mobile form factor, I began to outline the core features of Would Recommend.


This mobile application allows users to look up food options and check recommended selections based on food allergies and personal preference on a digital profile.​

Users can also leave reviews and recommend food options to other users with similar allergies.


In addition to online resources, users wanted personal recommendations from people who understand their food allergy. We decided to establish an online community for users that incorporates gamification.

Users could earn badges and advance levels the more they leave reviews. These reviews can be used as helpful recommendations from others who have similar allergies.


We uncovered another pain point in navigating to the restaurant: usually involving opening a dedicated navigation app to see where a potential dining option is relative to current position.

This iteration consolidated the different systems so that users can more seamlessly obtain information for making a decision.


‍Having created our basic prototype, we sought to evaluate it with professional users. Reaching out to experts of usability and mobile app design at Georgia Tech, we conducted heuristic evaluations sessions and asked them to accomplish key tasks with a paper prototype.

We observed what they were able to accomplish, what needed to be simplified, and what had to be clarified for the objectives.

From this data, I was able to develop the final high fidelity prototype.


I developed the final protoype in Figma with a revamped design, cleared up the gamification elements, as well as placing more information onscreen while searching for and rating restaurants.


During onboarding, users mentioned that using a dropdown menu would be more efficient to select cuisine preferences rather than manually entering them due to using a dropdown menu beforehand for allergies.

I also reduced the size of text fields to allow for the keyboard and complete button to fit within the screen size.


Our original prototype used solid colors as a placeholder for different types of cuisines on the home profile page. However, during our usability testing with experts, they suggested to see the name of cuisine in text, as users may not be familiar with country flags.

In addition to adding text, we decided that iconic pictures of cuisine would help distinguish different types of food.


Users were confused from the gamification aspects during testing, like badges and level progress. The presence of badges did not communicate what rewards users earned by posting reviews.

This confusion was addressed by adding a dedicated Badges section on the home page with reviews as well as rewards. In addition, listed are what and why badges were earned, reviews, and possible future rewards.


One of the key issues we uncovered through heuristic evaluation was a lack of flexibility.

The original prototype only supported one task flow, something that was overhauled by giving users more control, applying filters for rating, distance, cuisine, and price.

These filters can be toggled and arrange search results based on what they prioritize.


I redesigned the app to present more information than the previous iteration, since our testing showed that users wanted more statistics displayed onscreen to better their knowledge gathering of restaurants, like menus, photos, and reviews.

Rather than attempting to use a singular app for everything, tapping 'Get Directions' now opens a specific navigation app, such as Google Maps, to navigate to the restaurant with an already familiar interface.


User input showed that adding an alternative to written reviews would increase the ease of this task. Users wanted to be able to only give a rating instead of writing their own review.

This was added to the review process, with defined WOULD and WOULD NOT RECOMMEND buttons for quick input.​ In addition, users wanted to see the name of the restaurant they were reviewing while also finding a defined SUBMIT button, as such a button would confirm that their review was recorded.


From Would Recommend, I learned that users enjoy being in control of their experience, and that their imaginations and enthusiasm towards our project fueled our ideas and drove motivations.

Designing for users to empower and inform them is what my goals are as a product designer and it was satisfying to work with them to develop a solution.