A UX/UI CASE STUDY ON THE UBER APP
MY “ASSISTANCE” FEATURE FOR THE UBER APP
In my third week as an Ironhack student, we had another challenge. To analyze an already existing and highly adopted app and incorporate a new feature into the existing product. The Feature will be on an area of functionality and how to explored and compared it to user input.
In these four days sprint, for the first time, we were working individually. I felt a little nervous and challenged because I have never been working solo so far. I decided to go with an Uber app because it completely changed the transportation system. Focusing more on visual design, going further to UI design, and bringing all the learnings from UX design, my work will culminate in a high-fidelity prototype of a native app that reflects the best path forward based on research, iteration, and testing.
Let’s start with my project.
Discover
Uber is founded in 2009 and completed so far more than 5 billion rides. It’s available in more than 80 countries worldwide, and the state that uses it over the most is New York.
Business Analysis
Lean UX Canvas
Starting with analysis, Lean Ux Canvas set up the strategy to know who is the users, what is the business outcomes of the Uber app and, how I can better understand users’ benefits. Since this tool is a living document, I will make updates as I go through the Define process.
Competitive Feature Comparison
I started my research with a competitive feature comparison. I overview the competition on the market: Lift, Taxi, Subway, and Busses. What does Uber have to offer what others don’t and vice versa?
From there, I took information from the feature chart and laid out on a market analysis map where we could see further opportunities that we could capitalize on in our design. None of our competitors, as well as Uber, didn’t have an option to chose the driver, as well as to send a free ride to a friend. How can I use this insight? To find the blue ocean, to expand my research, this insight I use to compare them on Market Positioning Chart.
With this tool, I certainly better understand where I should focus on. The blue ocean is an opportunity that I believe Uber can enter with an additional feature. In this case, that would be a personalized option. To know that this is the right direction, I will dive deeper into the user research.
User Research
Survey
Surveys have been a handy tool for gathering a large amount of quantitative data. In my survey, I conducted 22 responses.
47% Decrease using Uber due to Covid-19
About 42% Would like to have an option to filter and choose their drivers
70% of users rate their ride
From the survey, I collected quantitative data, which gave me a bigger picture of people’s frustration and satisfaction. To be able to hear more people’s stories and experiences, and to discover pain points, I did six interviews.
I interviewed people who are already using the Uber app. Some of the pain points are :
“I don’t feel safe to use Uber during Covid-19”
“ I canceled many rides for passengers not having a car seat. Why would you want to ride around with your child unsecured?
“Pair the drivers native language with riders who have the same native language.”
I was pretty shocked by some insights from the interviews. I would never imagine that people have an issue with their pets, child security, or the language barrier. With all this research, I was excited to move on to the next stage in the process.
DEFINE
Since this project, I’m doing remotely, I am able to have my sticky notes in the Miro tool. I organized them and have them ready for Affinity Mapping.
Affinity Mapping
Key Learnings:
Language difficulties
Google Map difficulties
Assistance with the bags
Child safety
This tool helps me to organized data research and have everything in one place, so I can better see the connection between similar insights.
Value Proposition Canvas
When we are focusing on the user itself, Value Proposition Canvas is another excellent tool for identifying customers jobs to be done, what are their pains and gains. How do they feel when they accomplish their job. And which pain points we should be focusing on.
As is Scenario
To better understand users’ steps and how they are using the Uber app, we broke it down into steps: need a ride, requesting for a ride, waiting, riding, and coming to the destination. Using this tool, we can better understand their mental models. And indeed, be prepared for the next step in our defined stage.
User Journey Map
The process of mapping their journey encourages and reminds you to consider the entire customer experience: their feelings, questions, and needs. It’s used for understanding and addressing customer needs and pain points. What is the user thinking about, and what are they hoping to achieve?
Anna is a user persona who travels a lot and using Uber after her trips, mostly from the airport. She needs a comfortable and pleasant ride.
But she has pain points. Such as: “I want the driver who helps me with my suitcases, and to know Englis as well.”
After identifying these pain points, I quickly wrote down some opportunities and ideas to use during ideation.
I synthesized the pain points into a problem statement.
Problem Statements
When you determine pain points, you can create problem statements, which turn into How Might We:
- HMW, pair our users with the right driver?
- HMW, keep our users safe while using uber during COVID-19?
- HMW, simplify the options for pick up?
Turning problems into questions makes the ideation phase easier.
IDEATION
When you are working on your project by yourself, the Brainstorming process is such a challenge! It was the most challenging phase of my process because there is no other who can brainstorm with me under limited time. That’s why the HMW statement has to be so clear and creative so you can brainstorm quickly.
DEVELOP
During the process, I researched the Uber policy. It clearly stated that Uber does not tolerate discrimination against riders or drivers based on race, religion, national origin, disability, marital status, gender, identity, age, or any other characteristic protected under applicable federal or state law.
One of the pain points of users was the language barrier. Having that in mind, I couldn’t include that further into the developing stage because that would be against the uber discrimination policy. I learned that no matter what we do, we should always check rules and regulations.
MOSCOW METHOD
The Moscow analysis requires breaking down all story points into four groups.
Must: These features are mandatory. Neglect any of them, and the current sprint most likely fails.
Should: Features here can be described as significant to have, but not a top priority.
Could: These are small-scale improvements that don’t take considerable resources, but they aren’t essential.
Won’t: Sometimes, the “W” in Moscow is used to stand for “Wish” instead of “Won’t.” But always these items are of the lowest importance.
After prioritizing the features, I was able to define the products necessary to make my idea work, in addition to the gain creators and pain relievers on my
Value Proposition Canvas
The value proposition canvas goes around the concept of “jobs to be done’. We can focus on this question through the canvas. What is the product or service that new features will have that will alleviate pain and create a gain?
Jobs to be done :
When a users need a ride, they want to request a Uber who fully accommodate his needs and provide them safety and security, so they can reach their destination on time, feeling comfortable and safe.
MVP
To make it clear how reveal solution solves user’s needs based on data, just quick recap:
- “Does he have a child seat?”
- “I want a driver who will help me with my suitcases.”
- “Does he have a child seat?”
OUR MINIMUM VIABLE PRODUCT IS THE NEW FEATURE THAT MAKES IT EASIER FOR USERS TO PERSONALIZE THEIR RIDE. BE ABLE TO REQUEST A RIDE WITH ASSISTANCE, WHETHER IS THE CHILD SEAT, SUITCASES, WHEELCHAIR, COVID PRECAUTIONS, PET OR 3D MAP.
From this MVP, the new Feature will be Assistance. That would be a personalized way of requesting the ride that both driver and rider will know in advance are they are suitable for that ride or not. If the driver is not pet friendly and can not carry heavy suitcases, he wouldn’t be pair with the rider. And who is, will know in advance what he should expect.
User flow
To make it simple, work with a new feature, Uber riders are choosing Assistance and from there selecting all that he needs, and confirming pick up. If not, they will go to confirm without choosing any assistance.
DELIVER
Lo-Fi Prototype
Learned from the past project, I made a lo-fi prototype on the paper, and it was quick and straightforward. Looking at the original app, I was following the flow, until the new feature page, which I blend it into the existing app.
I sent the prototype to Maze for testing. It was 7% miss clicks and 85% success.
The results help me to add one more step into the prototype. I learn that all the steps should be clarified and simple.
Mid-Fidelity Prototype
I corrected everything from the previous testing and made a mid-fi prototype.
And from there, going to the testing through Maze, with the instruction:
You need a ride with uber xl, to go to work, and you will need Assistance with the suitcases. That’s how the users will know where they should click. To collect as many users as required, I posted on the groups under Slack Channel. And I have an amazing 15 testers! I was enjoying to see how people performed and to see the results.
It was an 87% success rate.
The only slide with the misclick was this one. Users were clicking on the map and on the confirmation letters. One of the solutions is to put a smaller text format above the Nexxt button and the map.
Atomic Design Inventory
That’s the logo that I downloaded from the home page, as well as font size. I wasn’t able to find the Uber Ui kit, and that’s why it was hard for me to imitate the design of the Uber app. For my new Feature, I use the icons from the Noun project web site.
Hi-fi Prototype
I tried to use the same font, same style, and buttons to blend the new Feature into the old design. It was a bit challenging and time-consuming but on the other hand very rewarding seeing my prototype at the last stage.
Here’s a link to my presentation if you would like to see a live walk through of the hi-fi!
Success and Failure Metrics
Success and Failure Metrics are crucial for ensuring UX design decisions are made and evaluated using adequate evidence rather than opinions.
The new Feature will have success through these metrics:
- High completion rate
- High DAU & MAU using the new Feature
- Returning Users
- Low task completion time
And we will know if the Feature is a failure through these metrics:
- High completion time
- Low DAU & MAU
- High churn rate
- Users don’t Use Feature
Knowledge Gaps
If I didn’t have only for days to create this Feature, I would spend more time on Usability testing and set up the interview to better understand why and how people are using this app. Furthermore, I don’t have extensive experience with Adobe XD. Working with the tool, I recognized how much I had improved by the end of the design process.
Next steps
-Test hi-fi prototype
-Continue to add earlier proposed Feature and test it
-Learn, research, and test
Key Learnings
Some of the Key Learnings are definitely to improve and practice Adobe XD. Also, if you work for the company that you are implementing the new Feature, you want to check their policies. Additionally, believe in yourself and seek help from your colleagues.
Thank you for reading my case study. If you have any questions feel free to leave your comments below, or you can reach me at Linkedin.
