Gingerabbit

Eat Smart

The Problem of Finding Healthy Food When Dining Out
The idea for Gingerabbit first came about out of my personal frustration and pain point of finding healthier food options while dining out, particularly during the busy lunch hour. It soon became obvious that I was not the only one facing this problem.

Role: Product Design         Year: 2016
Understanding the problem
Research shows that the average Singaporean eats out at least 4 times a week. Eating out is an unavoidable part of the lives of busy working adults, even health-conscious ones. Our competitor analysis shows that while many nutrition-focused apps provide the ability to track what users eat or show them healthy recipes, almost none can show them where to find food that matches their health goals when they are dining out.

Target audience: The health-conscious busy working adult. We asked our target audience to better understand their pain points, motivations and habits. Here are some key observations:
01
Lack of nutrition information listed in menus — harder for health-conscious diners to determine the healthiest options.
02
Different diners have different health goals. Some need high-protein meals. Some want to avoid transfats at all cost. Some prefer low calorie options.
We mapped out our observations from different stages of the user journey:
Pre-meal experience
Deciding which restaurants to go to or which item to pick from the menu that meets their criteria or deciding which are the healthiest dressing to pick with their salad.
Post-meal experience
Keeping track of what they eat.
Daily challenges
Staying hydrated throughout the day, figuring out what are the calories of their meals, figuring out where to find healthy snacks.
Prototype
The solution needs to make sure the key pain points are addressed. It is also clear that it has to be hyper-local and mobile focused.

After a few rounds of sketching and wire-framing with the team, I designed an HTML & CSS prototype which allows users to browse and search for food options near them, based on the health goals they pick. The early prototype helps us visualise and road test our designs, get feedback and iterate from there.
Branding and Tone
A friendly, approachable vibe — that's what we wanted for our brand. Ginger is known for healing qualities while rabbits move briskly and hop from place to place; they are also playful by nature. These considerations, and domain name constraints, led us to Gingerabbit.

Warm, Fresh. Friendly. The 3 keywords used to create the moodboard encapsulates the vibe we aim for in visual design. This sets the tone for the language we use in user interface, emails and marketing collaterals. I created a style guide for the main design components.
We iterated the early prototype and fleshed out the design for the mobile app. These product decisions were made:
01
Just show content types that help users make a dining decision or narrow down their choices. Don’t overwhelm users with information.
02
Don’t force users to sign up for utility features such as search and browse. However, they do have to do so for other features such as saving dishes, get personalised caloric intake and so on. This was a hard decision to make, but we went through with it to make onboarding easy and immediate for first time users.
Every feature has to either solve a real problem for our target audience or improve user engagement or adds delight to the overall user experience or all of the above.
We outlined our product roadmap and prioritised features based on this principle. Our core features such as browse and search for healthy food are not going to be enough for long-term user engagement which is why we included some features with longer-term user engagement in mind in version 1. Here are some screens from version 1, which helps diners find healthy food nearby:

Home

Search by goal, location, cuisine type. Browse by goal.

Dish Detail

Get personalised nutritional breakdowns of the dishes.

Profile

Get personalised daily recommended calory intakes, set water reminders.

Chatbot

For now, the chatbot can answer basic queries such as nutrition info for common dishes and give contextual tips.
Version 1
We shipped the first version on the iOS and Play store in April, 2016.
It allows users to do the following:
Search and browse for dishes based on goals, location and food type.
Know how much total daily calories, protein, carb and fat intake users need and how suitable each dish is based on a user's personal needs.
Set water intake reminders to help stay hydrated throughout the day.
Get nutritional info of common local foods and other nutritional queries answered.