A mobile app to help users find restaurants which fit
restrictions based on a match score and personalised reviews
Finalist: Convergence Innovation Competition 2017
though there are so many people who have some dietary restriction or the other, they have
neglected for long and don't have a medium to find dishes that fit their dietary restrictions.
the end, they pick the safest option on the list, which mostly is a "Veg Salad". The aim of this
project is to
help these users find meals at a restaurant that fit their dietary restrictions.
A mobile app that shows list of restaurants compatible with users dietary restrictions sorted
(by default) on
customized score for each restaurant. This customized score is based on other users
ratings as well as dishes at a restaurant that fit users dietary restrictions.
Conducted contextual inquiry and interviews sessions
Designed the survey
Took part in affinity diagramming session
Created low-fidelity and mid-fidelity screens
Created interactive prototypein Invision
Created evaluation plan
Conducted usability testing sessions and feedback
initial goal was to understand issues students face while grocery shopping but our initial
interviews and observations led
pivot to a more pressing need - inability to find restaurants to accommodate their dietary
What role does experience with
restriction play in their
What is the user process while
What kind of influence do outside
their decision making process?
We deployed the following research methods to answer the above research
Observed purchasing process in gluten-free section of the store
10 interviews to understand in-depth the issues faced by users
In this phase, we transformed our research into user needs, behaviors
We found user needs through affinity mapping and task analysis and identified user pain points.
needs saw a few emerging behaviors
amongst users, which were represented using Personas. These behaviors were categorized into groups
Vikkis, Vishnus and Graces. We then generated storyboards and customer journey maps to aid design
User Pain Points
Issues understanding different
ingredients due to unfamiliarity or scientific terms being used
Social stigma faced due to
being looked down upon because of dietary restriction
Language barrier due to
factors like noise or difficulty with the language
Through careful analysis of our research, we identified behaviorial
differences between users. These differences were mainly based on age, familiarity of the area,
barriers, reasons for having dietary restrictions, time since dietary restriction and their
These personas went through different emotional journey through their process of ordering food which
represented using customer journey maps. Customer journey maps helped us set expectations within
the team and a
emotional state that we wanted to aim.
Ideas were organized on a 2D map and were rated based on how well these designs matched the usability
forth in our affinity diagram - low cost, discreet, responsive and quick
to use, and clearly able to label ingredients (and how creative we thought they were).
After going through this process, we picked three ideas with the highest ratings – “QR”, “AR”,
Idea 1: QR APP
An outdoor restaurant signboard system that uses QR codes so that
a user could scan the code with their
phone and get an instant rating of their compatibility with that restaurant's menu.
Idea 2: AR APP
An AR APP that allows a user to scan the menu with their
The app would then provides information based on the menu items and the user's restrictions.
Idea 3: Kiosk
A Kiosk placed in a public setting around several
Where a user would be able to choose a meal from all compatible available options nearby them through
We created storyboards to fit these three ideas in different context as per our personas. This
validate that our ideas were relevant to the personas and helped us communicate our ideas across
users to get feedback on these three ideas.
To decide on which idea to go by, we conducted feedback sessions to understand
Pros and cons of each idea to explore the opportunity to get feature-level feedback to
ideas later on
Willingness of the user to create a profile on the app and provide personal information
Any scenario in which user's naturally thought of using this app to cover use cases, the
might have missed
Users wanted fine-grained distinction
dietary restriction as being a vegetarian meant different things to different users
Neutral to negative about creating
profile. Users didn't want to share their personal details in order to use the app
People bring a lot of expectations
Yelp. Users wanted reviews to be on our app and said they would visit Yelp to look at
reviews since our app didn't have any
Negative feelings towards using
Users felt that it was an overhead to use QR code
Hesitant about using AR. Users
they weren't comfortable using AR functionality in public
Users imagine using it in a group
setting. Users spoke about scenarios where they would use the app while going out in a
FEATURE LEVEL DECISION
After the feedback session, we decided to take feature level decision as we didn't want to
discard features just because people did not like how the way feature was presented.
Score include reviews
Score include no. of dishes
Reviews for user's restriction
Score per menu dish item
We created mid-fidelity prototype without adding colors and asked an expert to review our
got two main takeaways from this session.
TAKEAWAY 1: The expert had issue understanding what the restrictions meant in
didn't understand the sub-categories provided in the mockup on the left of the image.
we decided to remove sub-levels and show the restrictions at all same heirarchial
TAKEAWAY 2: The expert didn't understand what the legends meant. When they
categories, they understood what the legends meant. Hence, we decided to provide more
instructions to make the legend clear and have one menu category open by default.
Overall, I was happy with the outcome of the project given the constraints. Through this
project, I understood the importance of following up on leads found in user interviews
being scared to pivot. During our brainstorming sessions, I realized that sometimes an
the best solution and whenever in doubt, we must always refer back to the data.
evaluation phase of the project, I realized that it is impossible to satisfy each and every
If given more time, I would have liked to focus more on reviews and projecting them to the user
in more aggressive way. The current system is very passive.