In summer 2015, I had the opportunity to work with a student research team during the Research Methods in Interaction Design course at the School of Visual Arts. Our instructor Jodi Leo, Executive Director of User Experience at Critical Mass, led us through a four-week course wherein we collaborated with the Research team at Uber in an effort to optimize efficiency for Uber drivers during the pick up at the JFK airport.


Project Description

After a class call with Sam Eldersveld, Director of Operations Research at Uber, we learned that, Uber has a strong presence over the yellow taxi – with the exception of NYC airports. Historically, Uber drivers have circled the airport waiting for passengers, causing a bottleneck for other drivers at the airport. Yellow taxis, on the contrary, have the taxi queue directly outside of the airport, which optimizes their efficiency and wait time. Fortunately, Uber was recently given their very own parking lot at JFK. As the drivers pulled into the lot, their vehicles were logged via GPS satellite as they waiting for the next customer to order a taxi. 

The problem is that, since its implementation, Uber drivers have been waiting in the lot on upwards of four hours at a time – all without knowing their sequence in the queue. This causes Uber drivers to lose time and money. 

As we gained experience on field research, research methods, and different technologies throughout the course, our final project was to consolidate the most pressing barriers to picking up passengers at NYC airports for a research presentation. 



My Role

I conducted interviews with Uber drivers, conducted secondary research, developed personas, project management, synthesis, concept/use case design, and designed the  presentation narrative.



scope, APPROACH, and rationale

My team conducted both secondary research and ethnographic research. Considering the time constraints of the course, all of our research was qualitative.


Before the field visit to speak Uber drivers at JFK, we scoured the web to learn more about their attitudes and behaviors of Uber drivers and their customers. Through multiple blogs, we discovered that drivers believed there to be a level of general arrogance form many of the rides. 

These findings offered a level of driver empathy once it came time to speak with them during the interviews. We also considered that since most people in the airport are in a rush and are comprised of a certain privileged class, this might also be a cause. As we delved further into the research process, this assumption was confirmed.


Once we arrived to JFK Airport, we used AEIOU (Activities, Environments, Interactions, Objects, Users) templates as a framework to gather notable findings. We also created facilitator guides and screeners. 


Our group took the research even further and found additional Uber drivers to speak with. We used co-creation to help brainstorm ideal solutions that would mitigate the waiting time in the Uber lot.

Kevin (renamed for confidentiality purposes) was our key interviewee. As we hailed down and identified our Uber driver, we negotiated an untraditional ride: circling around the JFK airport for a 20 minute interview session. 


After the interview, we designed a persona based on our talk with Kevin and three drivers that we talked with throughout the project. Just to note, there are other personas within the Uber driver community (young, single, female, temporary, etc). In the context of perfecting the pickup at JFK airport, these key goals (below) apply to all Uber drivers.


We met after classes and on Google hangouts to go over our project scope, field visit notes, and interview synthesis. A few themes we began to build upon:

  • While in the Uber lot, Kevin (Uber driver) has no insight to his position in the queue amongst other drivers
  • Kevin waits for a call in the Uber lot for up to 3 hours
  • He dislikes his job because of the long hours and frequent lack of appreciation from customers
  • There exists an Uber community, but he is not part of it
  • He dislikes the pick up process, but airports are his most lucrative pick up location

We took the research we had completed so far and began to segment the Uber driver journey. By creating a service map, we were able to visualize the complete end to end journey and look for opportunities to optimize the pickup process. We also designed experience maps for the customer side as well. While user acquisition was not in the explicit scope of this project, we began to consider ways in which we could incentivize the use of Uber over yellow taxi once the user lands in NYC – an equally important part of the solution.


Research Findings

After consolidating all the data from our user interviews, the team began laying out the linear journey for the driver, searching for opportunities to build upon. After further brainstorming, we confirmed that the Uber lot is not making drivers more efficient. We saw this as an opportunity to design a better system.


Considering Uber's business goals and what we found during research, these are the three most common themes that we uncovered:

  • There is currently a prolonged wait time due to the implementation of the Uber lot.
  • There is a difficulty to identify drivers once Uber drivers arrive to the airport. Since there are multiple terminals for pick up and two floors at JFK, there is an opportunity to use landmarks to help streamline the identification/confirmation process for Uber drivers.

Due to city regulation, Uber drivers are not allowed to park in the same areas that yellow taxis park. Initially, we saw this as a challenge, but through our solution, we believe there is opportunity to build the reputation of Uber with select business professionals and frequent flyers in the city – eventually trickling down to less frequent flyers. 



Advanced booking system

The impact of the Advanced Booking System (ABS) has the potential to reduce driver wait time and maximize efficiency for Drivers while on shift. By matching the demand for Drivers and Riders, Uber makes more money by having more drivers are on the road at any given time. Driver/Rider pickup point can be clarified in advance, perhaps using Uber suggested pickup point map, which will assist both the Driver and Rider. NYC Airports are among the most lucrative and concentrated pick up locations for Drivers. This market is still uncharted territory for Uber, but with this the proposed ABS, there is opportunity for market efficiency. 


The components to the ABS are as follows:

User Acquisition: By leveraging existing partnerships (Google) and creating new ones (direct airlines, airline booking sites), Uber is positioning themselves right were the customer is. When booking airfare online, imagine being able to book your Uber at the time you book your flight. Also, when navigating to the airport via Google Maps, what if the rider was able to book an Uber for when they arrived back home.

Promotions: Uber already does heavy promotions around its service. This would be an easy and cost effective way to incentivize riders to use Uber exclusively when they are at NYC airports

Driver Interface: As advance Uber requests are made via the user acquisition and promotion strategy, these requests will be filed into the driver interface – the new Uber Lot. Drivers will no longer have to wait for hours on end for riders. They will know exactly who they are picking up hours beforehand. 

Rider Notification: using geolocation, there is opportunity to use specific landmarks within the airport to help riders and drivers meet at a centralized location. We believe this will optimize the pickup process significantly. 



Our team (below) pitched our research and recommendations to the class and really valuable feedback around the viability of our solutions. The feedback to focus on the functionality and flow of the driver interface is reflected in the iterations that have been made on this document.  


Project Details 

Tasks: Interviews, User research, UX Design, Acquisition design
Company: Uber
ClassResearch Methods
Instructor: Jodi Leo
Team: Sicong Chen, Meredith HamiltonSara Lim, James Vanié

Project Deliverables

• Sketches ( design iterations and user flows)
• Interview Footage, Synthesis, and Findings
• User Acquisition research
• Design and functionality recommendations proposal deck
• Final assets (presentation poster board)