How to ensure passengers at JFK airport have a good pickup experience?

Project Details

Timeline: 5 weeks. This project was completed through the summer 2015 MFA IxD Program at SVA working with Uber's Head of Research.

Tools: Omnigraffle, Sketch, Google docs, stickers, pen and paper

Team members: Celine Chen, Allison Heasley, Alberto Chen, and Ning Xu

Background:

When your uber car arrives at the airport, how do you know which one is yours without hopping into the wrong car? How many times have you held up your phone to match the photo with the same car approaching you? How to bridge the gap between the Uber app and drivers and passengers to ensure a better pickup experience? The problem we identified that there are issues of distrust in the accuracy of the application, the Uber systems that create a sense of uncertainty in the entire pick up experience between the driver and rider.


SOLUTION FOR INCREASING TRUST:

Improving Technology

  • Install iBeacons
  • UI modification (including terminal maps)

Standardizing Communication

  • Preset texts
  • Vibration Alerts

Assisting Riders in Visual Recognition of Vehicle

  • Display name
  • Car number

Managing Expectations and Creating Transparency

  • Visibility about wait time
  • Prompts and relevant information to rider

FINAL DESIGN

 

The prototype maintained the Uber original UI design and added features from user research to solve drivers' and riders' pain points

 App for Uber drivers

App for Uber drivers

 App for Uber passengers

App for Uber passengers


Design Process

DISCOVER

 

My role was a debriefer. From research and conversations, I found there was a fundamental issue of distrust in the accuracy of the application, the Uber systems, and between the driver and rider – creating a sense of uncertainty about the entire process.

FIELD CONTEXT

 

Car arrangements to ensure optimal quality of data capture

 Interview with the Driver

Interview with the Driver

  
 
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    Tech lead to sit close to the driver so she/he can take as many photos of the context as possible.

Tech lead to sit close to the driver so she/he can take as many photos of the context as possible.

DEFINE

 

To deeply understand the problem, my team and I worked on affinity mapping to review the trend patterns and differences in problems in different contexts.

AFFINITY MAPPING

 
  1. Break interview notes into smaller ones in order to make sense
  2. Combining multiple pieces into something new, e.g.: development themes, implication, opportunities

     Similarities in Responses

    Similarities in Responses

     Differences in Responses

    Differences in Responses


    DESIGN

    DRIVER USER FLOW

    IMG_4102.JPG

    RIDER USER FLOW

    IMG_4102.JPG
    rider user flow1.png