ExampleX.gif

UberEats

What is it like to experience Uber’s infamous UI while biking through the hills of Pittsburgh?

Vectors of Maps_Artboard 6.png

I biked throughout Pittsburgh delivering variable sized food from restaurants while analyzing the UI of the Uber Eat’s app. I was excited to explore the city on two wheels and experience Uber’s infamous UI firsthand. These are all the places I delivered to over the summer.

A Day in the Life

In Screenshots

These screenshots outline one full delivery, from accepting the delivery request to completing the trip.

By the Numbers

Boost Zones

Restaurants within a boost zone (roughly approximated by the red areas) had a significantly higher delivery fee; 32% of my total pay came from the extra boost charge. Every restaurant I ever delivered from is shown below, with red restaurants being boosted, and black being not. While most restaurants I picked up from were boosted, roughly 20% of all orders weren't from boosted restaurants. 

Drop-off Locations

Each one of my drop-off locations by zip code is shown on the map below.

Through Delivery Sequences

The red navigation lines denote "paid" distance traveled, while the black navigation lines denote "unpaid" distance traveled. Uber only pays for the distance between the restaurant and the drop-off location, excluding the distance it takes to travel to a restaurant. Idle time is the time spent waiting for a new pick up request.

Delivery Sequence A

  • Total time: 1 hour, 38 minutes 
  • Total pay: $8.28/hour  ($0 in tips)
  • Total idle time: 4 minutes
ExampleX.gif

Delivery Sequence B

  • Total time: 1 hour, 50 minutes 
  • Total pay: $16.53/hour  ($7 in tips)
  • Total idle time: 27 minutes
ExampleY.gif

Routes

I mapped every pick up, delivery, and intermediary travel route in order to compare paid versus unpaid distance. The red navigation lines denote "paid" distance traveled, while the black navigation lines denote "unpaid" distance traveled.

Uber's Dark Patterns

Uber's UX was full of subtle design nudges which attempted, at times successfully, to influence my behavior. Some nudges were obvious, for example, an opt-in Arbitration Agreement intended to prevent legal action against Uber, while others were more subtle.