Case Study: An App Redesign for Uber Driver
1. Introduction
There is no doubt that the user experience of an app is an important factor that directly impacts the business’s performance of platforms like Uber. Moreover, the UX plays an even more important role when the customers use the app as the only point of contact to access the services. This case study focuses on the study of enhancing the user flow for drivers in finding rides more easily so that it reduces the wait time for both, the driver and the customer. It also focuses on assigning rides to drivers to make their day at work the most efficient.
All in all, this would:
· increase the overall sales for the business,
· increase the per-day earnings for the drivers and
· increase customer satisfaction due to less waiting time for rides.
1.1 Glossaries:
Driver: The person who rides the Uber taxi is called a Driver.
Rider: The customer who uses the taxi service from Uber is called a Rider.
Hot-spot areas: High-demand areas for drivers to get rides.
1.2 Primary Objective of the Case Study:
To illustrate the process of redesigning the Uber Driver app with a focus on enhancing driver efficiency from securing to completing rides.
1.3 Background Context:
Uber, is a global transportation technology company, that connects potential rides to drivers to complete the rides through its rideshare service. Founded in 2009, Uber has revolutionized the taxi industry by offering a mobile app that allows people to easily and effectively request and book rides. The main idea of developing this app came back in 2008 when the 2 founders noticed that they couldn’t get a taxi on a cold winter evening in Paris (“Uber Newsroom”).
They developed the Uber app which lets people book a taxi with a seamless tap on their smartphones (“Uber Newsroom”).
While Uber connects riders with drivers, the Uber Driver app connects the drivers to the riders seeking services from Uber.
The Uber and the Uber Driver app, both work hand in hand as they share the same database for scheduling and booking rides. The process flow booking a ride to completing the ride can be broken down into 4 main sub-parts:
1. book a ride
2. accept the ride
3. pickup
4. deliver.
The flow of the above 4 main sub-parts, along with their contribution to both the apps (i.e. Uber App and Uber Driver App) can be understood in the below illustrated Gantt Chart.
1.4 Overview of the case study:
The below diagram illustrates the entire plan of how the case study was planned and executed from start to end.
2. Discovery of the problem
The discovery phase is the initial stage of UX design. It is the process of identifying challenges encountered by the users in the interaction of the product or service. It entails in-depth investigation and user research aimed at recognizing specific pain points and obstacles. This foundational phase is crucial for creating a user-centred solution that prioritizes addressing deficiencies in the overall user experience. It serves as a vital step in developing designs that not only tackle existing issues but also resonate with users’ requirements, guaranteeing a more efficient final product.
2.1 How did this problem come into the picture?
The story begins with a simple Uber ride. One day, my booking took an unexpected turn — waiting almost 10 minutes for confirmation and an additional 15–20 minutes for the ride to arrive. Curious, I struck up a conversation with the Uber driver, discovering he, too, had waited 15 minutes for a ride after finishing his previous one. To add to it, covering a considerable distance took him another 15–20 minutes due to an extended pick-up point. This personal experience shed light on the real-world challenges within the ride allocation system, prompting a closer look and a deeper understanding.
I then took the conversation further to find out more about the problem. These are the key insights that I got from that conversation:
2.2 A brief explanation of how the allocation of rides process works at Uber. (Uber Technologies, Inc.)
When you request an Uber ride, it’s more than just finding the closest driver, it’s an entire process that takes action. Uber takes a moment to assess all nearby drivers and riders, creating the perfect match for everyone involved. It’s not just about proximity; it considers factors like traffic to ensure a smooth experience.
In the early days, it was a race to the closest driver, but now Uber waits a bit, gathering potential matches to reduce the average wait time for everyone. So, it’s a thoughtful approach, making the ride experience smoother for all users.
Uber is always working to enhance this matching process, prioritizing efficiency for drivers and riders alike. Behind the scenes, they’re committed to minimizing wait times and optimizing driver earnings.
2.3 User Interviews
In the “User interviews” phase for my Uber driver app project, I had friendly chats with actual drivers. I interviewed 5 Uber Drivers and asked them about their experiences — how they decide where to go, what challenges they face, and what they’d love to see in the app. It was about hearing their stories firsthand to make the app a perfect fit for their needs. These conversations brought a real driver’s perspective, helping me shape the app to be not just practical but something drivers truly enjoy using. It’s like turning their feedback into the key ingredients for a smoother, more driver-friendly Uber experience.
Mentioned below are the questions I asked them.
Understanding Current Decision-Making:
· How do you currently decide where to position yourself to maximize your chances of receiving ride requests quickly?
· What factors influence your decision on where to wait for ride requests?
Awareness of hot spots:
· How do you stay informed about areas with high demand for rides throughout the day?
· Do you find it difficult to figure out how many people want rides in different parts of the city right now?
Efficiency in Ride Allocation:
· Can you share an experience when you got a good amount of rides throughout the day?
Preference for information:
· What type of information would be most helpful for you to see regarding ride demand in the app?
· Can you describe any challenges or frustrations you encounter in finding rides in certain areas or times?
· Are there specific scenarios where you find it challenging to make informed decisions about where to position yourself?
Interaction with App Features:
· How often do you interact with the app while driving to check for ride requests?
Experience with Similar Features:
· Have you used other ride-sharing apps that provide features similar to what we are discussing?
· What was your experience with those features, and do you find them beneficial for optimizing ride allocation?
Feedback on Potential Solutions:
· What areas do you think needs to be improved in the app so that the user experience is better?
· Are there specific details or functionalities you would like to see in such a feature?
2.4 Problem Statement
3. Research
3.1 User Personas
User Personas are fictional characters representing diverse driver profiles for the user base. These personas encapsulate different driving needs and challenges, guiding us to address real-world scenarios and enhance the user experience.
3.2 Empathy mapping
Empathy mapping for the Uber driver app is like creating a simple picture of what drivers experience and how they feel, based on our conversations with them. It helps us understand their challenges and hopes so we can improve the app for them. By listening to what drivers share, think, do, and feel, we make sure the app is like a friend that truly understands their needs. It’s like having a friendly chat with drivers and using that to make the app more user-friendly and helpful
3.3 Competitor analysis
To redesign the app, it’s best to take a closer look at what others in the same field are doing. I explored how companies like Bolt, Ola, traditional taxis, buses, Via and Wheely handle things. It’s like peeking into their features which would help to learn from the best, fix any issues, and add better experiences to make our app the best amongst it’s competitors.
3.4 User Journey maps
To empathise with the user, it is important for we designers to understand the emotions and the feelings the driver (our users) go through throughout the journey. A user journey maps helps best to note down the emotions of the users throughout the journey and detect where best we can make changes in the journey to improve the users experience.
Task: To get a ride and complete it.
Carlos, an Uber driver decides to do some Uber rides one fine evening. He hops in his car and is now to start his Uber journey.
4. Ideation Phase
4.1 How might we’s
How might we’s is a super fun idea to create valuable solutions for the problems we have in hand. This decision making session can be found with the best explanation on the AJ&Smart youtube channel. (AJ&Smart)
Using this method I focus on generating multiple ideas for the problem we have to solve for.
These were all the ideas that came up when I did the how might we exercise for the above problem. The next step I took was to plot these ideas in a “effectiveness” vs “efforts needed by drivers to implement/follow” graph.
In the above graph I have defined the optimal range as those solutions which have the highest effectiveness and least efforts needed by the users to implement/follow.
These are the following solutions which fall under the optimal range for the 1st and the 2nd problem.
Mentioned above are the top 2 best solutions for problem statement 1, however, it won’t be ideal to list the nearby hotspot areas near the drivers location, as the driver would have to stop somewhere, read the list, and then decide as to which place to navigate to. Therefore, It would be ideal to show the driver heatmaps where he can understand the data and make a quick decision without the need to stop anywhere.
Mentioned above are the top 2 best solutions for problem statement 2, making the heat maps personalised for each driver would help in equally spreading out all the drivers so that every driver would get good amount of rides throughout the day.
4.2 User flow diagram
A user flow diagram is the ideal flow of how the user would perform a particular task with ease and efficiency.
5. Design Phase
5.1 Wireframing
After collecting all the data and synthesising it, I started with the wireframing phase. In this phase, I used all the ideas generated from the ideation phase and started placing them on the wireframe screens to make the designs more meaningful.
5.2 Hi-fidelity designs
With the help of the created wireframes, I then went for the hi-fidelity designs. The design system used here is same as that of the original Uber Driver app since it’s a redesign and not a design from scratch. Below are the screens designed.
5.3 Link to a clickable prototype
Here is the link to the Figma clickable prototype: Link
6. Testing Phase
Using my designs I conducted user testing on 2 users. User testing helped me get feedback for my designs in both: user experience and user interface. I encouraged my users to speak out loud what they felt about my designs as they walked through them. The feedback from the user testing was then used to re-iterate and finish the designs.
Note: The feedback gained from the user testing is subjective to designs only. There could have been more feedback given if the testing was done on the developed prototype.
References:
- “Uber Newsroom.” Uber Newsroom, https://www.uber.com/en-GB/newsroom/history/. Accessed 28 December 2023.
- Uber Technologies, Inc. “Uber Marketplace Matching.” Uber, https://www.uber.com/gb/en/marketplace/matching/. Accessed 4 January 2024.
- AJ&Smart. “Design Sprint WORKSHOP — (Lightning Decision Jam AJ&Smart).” YouTube, 26 October 2018, https://www.youtube.com/watch?v=33hBnZzoFAg. Accessed 6 January 2024.