Redesign the user experience of Lyft for the year 2030, focusing on future technology and anticipated issues related to that.
Timeline & Details
This project lasted a total of five weeks, and was a group effort by Cyrena Johnson and Hunter Simpson.
Research & Brainstorming
Future Technology Research
Lyft is primarily a smartphone app and is heavily involved with vehicles, and so our research involved looking into the future of both of those markets, as well as how the company is currently expanding.
Our first concern was in predicting the future of smartphones, as Lyft is primarily a smartphone app. Our initial assumption was that smartphones would be phased out and replaced in ten years, likely with some form of wearables or hologram technology. However, upon researching it we realized that as it currently stands, wearables are more likely to grow in use as supplemental technology, to be used in combination with smartphones. Even smartwatches and smart glasses are not likely to full replace the smartphones functionality, though smart glasses will become increasingly prevalent alongside AR/MR technology. Hologram technology, as well, is more likely to appear in the form of AR/MR in the near future.
However, even if smartphones are not replaced they are not likely to stay exactly unchanging either. Predicted changes include increased speed, battery life, and graphics, and the move to bendable smartphones, like the ones Samsung has been experimenting with for several years now. In terms of functionality, however, those changes are not likely to make a huge impact on how Lyft works. Therefore, the most important change to smartphone tech is likely the integration of AR/MR technology. This trend is already visible in current markets, and we predict that the use of MR will only continue to increase in the future. As a result of our research, we decided that smartphones, used in combination with smart glasses and AR tech, are likely to be the primary platform for Lyft in the future.
When considering the future of Lyft, the next main consideration was the future of automated vehicles. As it turns out, most ridesharing services already plan to switch to fleets of self-driving vehicles in the future. Lyft has completed over 5000 test drives so far in self-driving vehicles. It is likely that their drive to use self-driving cars in the future is connected to their sustainability and mobility focused goals as a company. Lyft has made pledges to commit to full carbon neutrality, 100% renewable energy, and increased accessibility of public transit. All of these goals are likely to influence Lyft’s future market trends as well, likely in the form of sustainable self-driving vehicles and reduced fares, among others.
After doing the initial research we conducted a long brainstorming session and come up with a wide range of potential concerns to focus on for Lyft’s future. This list was based on our own assumptions and Lyft’s company values. From this brainstorming session we created a list of questions to ask in a survey. In that way, we hoped to have a future plan for the company with a basis in the user base’s own desires.
Although we conducted small interviews and used hands-off collection methods as well, by far the most helpful part of our early user research was the survey we conducted online. The survey was 14 questions long and we got 60 responses to it, providing a fairly large sample size. The responses from this survey provided crucial insight on the main problems Lyft would face in the future. Below are some of the statistics gained from this process.
46.9% of respondents said their main concern with automated vehicles was safety.
36.7% of respondents said they primarily used Lyft when inebriated.
Only 5% of respondents said they did not feel anxious or unsafe when using Lyft.
Convenience, Low Cost, and Safety are the most important things to rideshare users.
Based on the survey results we got, we realized that the most recurrent and pressing issue for Lyft—and the one that would only increase in the future—was the need for comfort and safety.
This is especially true given the future of the related technology, and the move to a fully-automated Lyft fleet. Our survey results proved that the current population is concerned about automated vehicles, and therefore Lyft will have to make a concerted effort in the future to assuage those fears.
So what does that mean for this project?
As the problem we discovered is intrinsically connected to technological advances central to the future of Lyft, our process as a whole focused on testing the UI for those technologies. As a result of this, we did not largely focus on the current competition Lyft faces, or issues of primary demographics.
Once we understood our problem, the essential question to answer became what makes people feel comfortable? In the short responses we received on our survey, one common theme emerged: people want to feel in control. This in turn influenced our goals for the project, and the rest of our process focused on user testing with comfort and control in mind.
How does the user want to feel using the product?
1. Safe (physical safety, psychological safety, knowing the car won’t hurt them)
2. Convenience (knowing that the car will be there soon)
3. Trusting (that the car/driver will get them to the destination on time)
4. Ease (intuitively know how to order the car, no anxiety)
5. Comfortable (in the vehicle, not in danger)
What does the user want to achieve by using the product?
1. They want affordable and safe transportation from point A to point B
2. A solution to not owning a car
3. More convenience that public transportation and taxi services
Why is the user is trying to accomplish the end goals?
1. Be cost effective in their budgeting (saving money by not owning a car)
2. Have the convenience and financial flexibility of ordering a car
Solve current and predicted user discomforts associated with the Lyft process and future technologies through the use of augmented reality and adaptive safety features.
Over the course of this project our direction shifted directions several times, most notably in the beginning. During the early brainstorming and research processes, and before we settled on comfort as our main concern, we had many ideas on what to focus on that ultimately needed to be put aside. Given the scope of the project it made sense for us to focus on one objective, but we feel that any of these topics could make for interesting extensions in the future.
One large point we discussed was the future of affordable transportation. As of right now, Lyft is on the pricier side, and is deemed a luxury for those who can afford it. This is even reflected in our survey, where 23% of respondents said their Lyft use was restricted by money. (This was equal to the amount of people who stated that they used Uber instead.) However, this price point could change in the future. There are already some places in the US where local governments are subsidizing Lyft rides, and making them more accessible for the public as a whole. If in the future Lyfts could be made more affordable then they could even replace individually owned cars in a lot of circumstances. Ultimately, however, we decided not to pursue this idea because we recognized that having MR design for automated vehicles was something that would need to happen first.
Another point we wanted to focus on was sustainability. This was connected to the idea that Lyfts could replace individually owned vehicles in the future. If the future Lyft fleet was designed to used renewable energy and transport many people at once, it would provide a totally feasible way to reduce humanities carbon footprint overall. This idea was also in accordance with the pledges that Lyft had already made to achieve carbon neutrality, and therefore was highly likely to be implemented. We did not chose to focus on this topic, however, for the same reasons as before, but also because it was more focused on industrial design strategies than UX.
The user flow was a significant step in our process, as it helped us visualize how each part of the project would come together in the future. It also helped us better consider fringe cases and possible future problems for the app as a whole, which deepened our understanding of what necessary features would be, and how the system worked as a whole.
On this page are a few of our earlier sketches, which were helpful for us to visualize how future riders would interact with their Lyft service. These were completed before we started designing for the phone or MR, and served as our basis for inspiration.
User Testing Round One
Our first round of user testing made use of paper prototypes. We tested three different people, and had them walk through the whole process of ordering a Lyft and taking a ride. These tests started with phone mockup screens as users ordered their Lyfts, and then switched to fake MR glasses when the ride arrived. The MR glasses highlighted the car as it approached, and displayed a dashboard and an AI driver inside the car itself.
Round One Results
Overall we got very positive results on our first round of user testing and only lost a few points overall. Additionally, we were lucky enough to receive similar criticisms from all of our testers. Below are some of the results.
“The AI Driver is confusing”
“The buttons on the right side are too small”
“The pee break button needs a timer”
Lowest Ranking Stats
1. Headings/icons are clear and descriptive
2. Navigation/menu is used consistently
User Testing Round Two
For round two of testing we created prototype screens on sketch and tested them using InVision. We had a very similar process for the users on this round, asking them to order a Lyft and take a ride. However, because we changed some of the functionality, the tasks were slightly different and so we got different responses.
Round Two Results
We got even better results on round two of testing, and got full points on most categories. Again, we got similar results from each of our testers, which gave us a focus for our next round of changes.
“The button designs need more consistency”
“All the buttons should be on one dashboard”
“Add a prompt on how to switch between screens”
“The confirm ride button is confusing”
“The AI Driver is still confusing to me”
Lowest Ranked Stats
1. Buttons/links/icons were adequate sizes
2. Headings/icons are clear and descriptive
After the user testing ended, we went through several more rounds of iteration on the interface, specifically focusing on the MR dashboard that appears inside the vehicle itself. Below are two of the later iterations, showing how our design changed before the final.
Above are the three main screens from our first digital prototype. The users were expected to swipe left and right between them, and the dashboard remained the same across the bottom of all three.
This was the second iteration of the dashboard. In this version we consolidated everything into one bar and removed the extra screens entirely. This version lacked the phone, games, and apps buttons, which were added again in the final iteration. It also had too much color, was too big, and the map screen was too small.
A big change in this version was the switch from an AI driver to an AI voice instead. The driver was causing a lot of confusion, and speculation as to its necessity as well. Voice AI’s however, like Siri and Alexa, are more common today and would be more comfortable to the Lyft riders of the future.
The final designs for this project are displayed below, in the order that they would be used during the Lyft process. The user starts on their mobile phone, then switches to primarily using their MR glasses when the car approaches. Once they are in the car they can see the specific Lyft dashboard designed for their ride, which integrates information from their mobile device and the car itself.
We faced different challenges at different stages in the UX process. Our first major challenge was in honing in on a specific topic for this project. As stated on the concept evolution page, we had several directions we wanted to go in as a result of our brainstorming phase. Choosing one was difficult, because we felt that all of them were substantially important to Lyft’s future.
Another challenge was designing for MR, because there were no real screen constraints and it was difficult to conceptualize without any real way to implement it.
Making a futuristic design for the project as a whole was also difficult, because there were only vague notion of future design trends to go off of.
During this project we learned a lot about the UX process and the future of hand-held and transportation technology. Research was key for us, and without it we wouldn’t have been aware of our biases or been able to envision the technology we would be designing for. We also learned a lot about the future of AR and MR tech, and how different it was to design for that rather than for a phone or computer screen. It was also very interesting to understand even a bit of how transportation would change in the near future, and it will be cool to see if our predictions were correct or not.
In terms of UX, we discovered how important it was to start wide in researching and planning. Our solutions were the product of wide ideation. By trying to envision the system as a whole before honing in on specific parts, our final product was a lot stronger.