Coral

The Driver and Business Ecosystem | September ~ December 2019 (10 weeks)

My Role

I was the lead designer and UI/UX designer of Coral as part of Stanford’s Intro to HCI Design course. My team carried out the project through the Design Thinking methodology from needfinding to high-fidelity prototyping. I conducted user interviews, usability tests, heuristic evaluations, and designed the interface of the app.

My team won Best Overall Project and Best Demo at the CS147 Industry Project Fair. 

Overview

Many gig economy drivers (e.g. Uber, Lyft, and DoorDash drivers) face difficulty finding amenities such as bathrooms while working. Their current solutions include finding nearby gas stations, using the side of the road, or even using a bottle in their own car.

Similar to how coral reefs provide sanctuary and resources to marine life, Coral connects gig-economy drivers with small businesses that provide amenities in return for a potential increase in foot traffic and customers.

Needfinding

Gig economy has been growing rapidly in the US over the last few years, more than one-third of the population participating in the gig economy as of 2018. Among those 57 million Americans, around 1.6 million are gig economy drivers who use apps like Uber, Lyft, and DoorDash. Having heard the various difficulties drivers experience from the news and during rides, we decided to explore the world of the gig economy driver.

To understand the problems gig-economy drivers experience, we immersed ourselves in their work environment. We went to the San Francisco International Airport Rideshare Lot to interview drivers, and we conducted further needfinding during 30+ Uber/Lyft rides.

As a result, we were able to gather insight ranging from obvious struggles such as low pay and physical strains to their need for basic human decency and career fulfillment.

As a result, we were able to gather insight ranging from obvious struggles such as low pay and physical strains to their need for basic human decency and career fulfillment.

Define

Afterwards, we created point of view (POV) statements and how might we (HMW) questions to tell the drivers’ stories and discover the problem domain we want to focus on. Among the several POVs and HMWs we have created, we decided to go with the one below.

Ideate

Based on our HMW, we came up with potential solutions by testing our assumptions using experience prototypes.

Assumptions

We assumed drivers would be interested in seeing nearby accessible amenities, so we thought one direct solution could be providing drivers with an app that shows the locations of their desired amenities. 

But to provide them with the locations of the amenities, the managers of these locations should be willing to allow drivers to use the amenities. So, we assumed that the managers would be motivated to do so for the sake of more foot traffic in their stores. 

Experience Prototypes

We designed a couple of experience prototypes to test these assumptions.

For Experience Prototype #1, we marked all the locations of accessible bathrooms on a map of Stanford’s campus and gave it to Uber drivers and gathered their thoughts. Drivers reacted positively towards the maps we gave them and expressed that such a map would be especially useful in busy urban areas. 

For Experience Prototype #2, we laser cut a sign saying “Gig-Economy Driver Friendly” and went to stores on University Avenue to talk to the employees. The employees expressed that they don’t care too much about who uses their bathrooms. Although we couldn’t talk to many of the managers because of their absence, one restaurant owner told us that having some potential customers visiting his restaurant in empty hours could help his business.

Solution​

After reviewing results from our experience prototypes, we decided to create a driver and business ecosystem: businesses such as privately owned restaurants can upload their locations and amenities, and drivers can find the locations and leave reviews of their experiences.

Concept Video

We named the driver and business ecosystem Coral, and decided to design a mobile application that would perform 3 tasks:

Task 1: businesses publicize their amenities to drivers

Task 2: drivers see the locations of the amenities​

Task 3: drivers leave reviews of used amenities
 

Based on these 3 tasks, we created the concept video below.

Initial Sketches

With pen and pencil, we made rough sketches of possible interfaces for our solution. Some of the interfaces we thought of include voice control, list view, smartwatch, and map view. We decided to go with a map view as our main interface; drivers already use apps with map interfaces such as Uber and Google Maps daily, so the learning curve of using our map-interfaced-app would be very low.

Low Fidelity Prototype

To test basic functionality and interactions, we sketched out testable screens for the 3 tasks.
We made the screens below, and we laser cut a model of an iPhone to make testing more intuitive and friendly for the test subjects (drivers).

To accurately simulate a real-world scenario, testing was done during actual Uber and Lyft rides, an environment that the workers would find themselves in when using the app.

Testing the low-fidelity prototype yielded invaluable feedback that would be crucial for designing our medium-fidelity prototype. For instance, although most users expressed familiarity with the map interface, they were not able to complete certain tasks as they couldn’t find some of our unique features (e.g. amenity location icons). Also, users expressed difficulty during the review task, not understanding what exactly they were supposed to do and not knowing which icons were interactable. 

As a result, we learned that our design should be more user friendly and better reflect our value proposition.

Medium Fidelity Prototype

We addressed the above problems by designing a medium-fidelity prototype with Figma. To focus our app more on the end-users (gig-economy drivers), we changed our first task from uploading a location with an amenity to an onboarding process where the drivers customize the amenities they would like to see on the map screen. Some other changes include being more conservative with using color and making it clear what is interactable.

High Fidelity Prototype

After conducting additional user testings and receiving heuristic evaluations by the faculty and students of CS147, we designed our final high-fidelity prototype. We used Figma to refine the designs and interactions and then used React Native on Expo to develop a functioning prototype. 

Below are the demo video and some of the screens of the high-fidelity prototype. 

Demo Video (Prototype Made With React Native On Expo)

CS147 Industry Project Fair

Finally, we presented our work at the CS147 Industry Project Fair among 35 other teams from the class. Judged by 16 industry professionals, our project won Best Overall Project and Best Demo.

Reflection

The shocking and deeply emotional stories of gig economy drivers having difficulty finding bathrooms and sleeping in their cars for days on end to provide for their families motivated our team to build Coral. After countless user interviews and design iterations, we were able to develop a high-fidelity prototype of an ecosystem for gig economy drivers and small businesses. 

Working on Coral helped me take a step forward to becoming a product designer. The countless interviews and user testings I conducted helped me become better at talking to users and understanding their needs. The iterative design process from low fidelity to high fidelity taught me how to make and justify design decisions, and design intuitive user experiences and aesthetically pleasing user interfaces. Finally, working with a phenomenal team helped me become a better team player and recognize the importance of teamwork in such a project.

Gig economy drivers across the country still experience the problem of finding amenities while on the job that many of us take for granted. My team and I plan to continue developing Coral to solve this problem and positively impact gig economy drivers’ lives.