Humanizing the ride sharing experience: From design challenge to an app feature for Lyft
Case study fostering meaningful connections between drivers and riders, one ride at a time.
Project Overview
During a good part of the last decade, corporations, start-ups, small businesses and freelancers have been asking themselves, and their businesses, how to engage more openly in an honest conversation about the different ways to express gratitude in the workplace.
The brief
How might we improve the ride sharing experience to allow both drivers and riders to communicate more authentically while removing communication barriers in the fast paced shared-transportation environment?
Team and Award
This case study originated during OpenIDEO’s San Francisco Chapter’s design sprint for the Gratitude in the workplace challenge sponsored by the Greater Good Science Center. This submission was selected as a finalist to continue to the refinement phase of the design challenge, and ultimately recognized as a one of the Top winners and Grant Recipient. The entire process, from start to finish, has been an evolving study since completing the sprint phases in late 2017.
Now more than ever
With remote and distributed work at an all time historic high thanks to the unfolding adjustments of Covid-19 around the globe, it’s been clear gratitude in the workplace is now more important than ever.
So I decided to revisit this body of work during the summer of 2020 and translate the human-centered-design process to a UX/UI framework that delivers a solution that integrates into an existing digital service.
So why Gratitude? An opportunity
The practice of gratitude strengthens our relationships, improves our health, motivates us to achieve our goals and is closely linked to boosting our overall feelings of satisfaction with the tasks at hand, however small or routinely they might be.
When looking at gratitude in the workplace, our team focused on the gig-economy population, as we recognized they are the largest growing number of employers further removed from the traditional office environment. Moreover, when employees feel valued, it benefits both them and the company, as they are more likely to stay with the business when they don’t feel replaceable.
Design Process
This project was executed with a human-centered design framework, from empathy and ideation, all the way to prototyping and testing, while delivering a high-fidelity prototype.
My design process began with discovering and understanding the core issues of the users I’m solving for. Then I utilized various research methods to uncover the various challenges and pain points by users (both riders and drivers) during their daily interactions. I then combined as many ideas as possible in the ideation space to help ground the problem into actionable areas and converge on one or two key concepts.
From there, it was all about working with constraints and paying close attention to opportunities available within existing digital services, as well as thinking outside of the app for nudges that could improve this experience for users on both sides of the wheel. This part merged multiple rounds of prototyping and folding the solution seamlessly to minimize disruption. At the end of the process, I have a solid concept that’s gone through every stage of the process and has been validated with users.
Discovery
A big part of the discovery process was observing trends happening inside and outside the app of a ride sharing experience. In this phase I conducted various layers of user research including:
- Market research
- Competitor analysis
- Secondary research.
The goal was to contribute to our team’s understanding of what’s currently being offered by major ride sharing companies, and what are other ventures and startups looking to capitalize on to help improve the overall experience.
Describe
This stage was all about corroborating initial discoveries with what was learned in the field from multiple members and vantage points. Using tools like user interviews and mapping out the existing user journey where important tasks to identify pain points and understand best ways to move forward.
After in depth user research and interviews we were impacted by drivers saying things like:
“when they [riders] are all on their phones I feel invisible, like just part of the machinery to get them from place to place.”
This inspired us to come up with a solution that will humanize the drivers.
User Interviews
Next stage was interviewing users and customers across different ride sharing apps and experiences to get first hand validation on our assumptions. I decided our interviews will be semi-structured: guided by the interview script but the interviews will also be flexible enough to allow us to explore relevant topics raised by the interviewees. I suggested utilizing the “think out loud” interview method to get insights of usability and accessibility challenges.
I conducted over 5 individual sessions, and oversaw about 22 total interview sessions. Sessions were recorded and transcribed for specific themes and patterns in data. By speaking directly with workers on the field, on and off their shifts, we discovered insights that would eventually impact major design decisions down the line.
User Journey
As we were conducting user interviews, it became clear it was paramount to understand what was the current user journey and where could we make a difference? While simultaneously analyzing areas of opportunity in Lyft’s exisiting app ride experience.
Define
During our brainstorming sessions, recognition of insights and “how might we” exercises we understood the importance of that human connection is at the very core of our idea.
I looked at ways in which gratitude was expressed, either incrementally or in different kinds of acts to understand areas of opportunities. It was important to also consider who are users where, how this experience could be inserted in a real life scenario and ultimately how users would respond to this new feature.
Wireframes
It was time to roll our sleeves and start sketching with pen and paper what this experience would like and how it could create a meaningful impact in the ride sharing experience. As a group, we made multiple low-fidelity prototypes using pen and paper and uploaded the different proposals using Marvel App to test basic assumptions and findings.
User Testing & Challenges
We tested our concept by observing several drivers engage with the wireframes. Drivers gave us verbal on-the-spot feedback on every screen they saw. The main takeaways from our initial user testing were that drivers are more motivated by connecting with their passengers and improving the ride experience than improving their ratings.
Additionally we found that even though a profile feature already exists in ride share apps, hardly anyone fills it out because it is open-ended and requires too much effort. This led us to emphasize creating a profile feature that is simple and easy to fill out.
Right away, our pen and paper wireframes allowed us to conduct usability tests, and get quick feedback from conversations with riders and drivers.
Limitations
- Drivers who either barely speak English
- Drivers were uninterested in the prototypes
- Drivers that just wanted to complain about other aspects of Lyft
- Drivers are multicultural and from many different backgrounds
- Gratitude means many different things to many different people
Feedback
- Engaged drivers on their shifts, while we were partaking on a ride experience ourselves.
- We tested what level of engagement were drivers comfortable in engaging with
- Inquired aspects about sharing of personal information in order to bridge the gap between driver and riders, while promoting a safe space to create meaningful encounters that will lead to a more gratuitous exchange.
Observations
- Drivers log in and out of the app throughout their shifts
- Language can be a difficult topic for both driver and riders
- Vulnerability and openness are key stepping stones towards gratitude
- Allowing a safe space within the car is the most important quality of a ride
- Some people don’t want to share their story, in that particular scenario.
Persona and Experience Map
Following a first round of ideation we also formulated various personas and scenarios to further test our preliminary assumptions with different case scenarios. Using this tool during the ideation stage, gives a common and concrete vision of who the customer is. We can establish personality attributes, and places in which different people can experience in the frameworks of where the product will be used. To compliment the persona, I also included an experience map to visualize the end to end experience a user might have with our idea over time. For this iteration it was important to insert the before-the-ride experience, as well as at the end of the shift or ride.
Deliver
Drivers feel that they receive gratitude when their riders treat them as humans, rather than service providers. Drivers enjoy when riders engage in a conversation and express appreciation towards the drivers. Our solution does not force riders to engage in certain behaviors, but rather aims to change riders’ perspective on drivers. When riders are exposed to the human side of drivers, it is natural for them to express gratitude towards them.
Lo-Fi Prototype
After arriving at a comfortable prototype, we got together as a group to review the evaluation criteria of the design challenge, understand what our sponsor was expecting, and what the jury and sponsoring organizations were looking for.
For this stage, our team created a UI refined prototype using Invision Studio. I was in charge of highlighting the steps of the experience, as well as bringing the research and interview insights to shine in the steps of the mobile experience.
Hi-Fi Prototype
After reviewing Lyft’s design and material guidelines, I recreated the app’s pop-up, profile and personal info sections. And seamlessly included the proposed feature in the brand’s experience using Adobe XD.
Learnings
Imagine if there was a common language for gratitude?
The key measurements that define gratitude are highly indistinct and require a great deal of context such as a person’s genetic disposition for happiness, their lived experience, their social disposition, etc. No one person receives or distributes gratitude in the same way, but there are commonalities that inspire and promote well-being. Perhaps if employers prioritized the well-being of their workers, they could create environments of increased productivity, health, and happiness. Being seen, heard, and understood is at the core of gratitude.
Reflections
Our scope of work on gratitude was purposefully small. We chose to take a complex challenge and shrink it into something that could be experimented and experienced. We conducted mostly qualitative interviews and were not able to conduct as many qualitative research due to our time constraints and the limitations of the subjective nature of the content. The level of engagement depends on the mood and the willingness of both participants. We mostly focused on the feedback of the drivers and less so of the riders. We realize that considerable thought should be placed on the “opt in” component of the game. Both parties would need to agree to opt in.
Lessons
- Take a complex challenge by starting small.
- Do the research you can, with the time you have.
- You are not your user.
- Test and design by observing in real time.
- Be open-minded and nimble to change.
- Get to know your existing problem inside-out.
- Offer opt-in solutions that feel natural.
Conclusion
This project could not be possible without the OpenIDEO SF community and direct involvement of team members including Nicole Sorci (UX Researcher), Hayley Somervile (Product Designer), Amy Lin (Product Designer), Flora Massah (illustrator), Alena Egorova (UX Designer).
Thanks for reading if you made it all the way here! I would love to hear any feedback or thoughts you have about this post or answer any questions. Please feel free to leave a response below or shoot me an email directly to francescostumpog@gmail.com. I’d love to hear from you!
Sources
- Adam Smith, Jeremy, and Emiliana Simon-Thomas. “How Grateful Are Americans?” Greater Good, greatergood.berkeley.edu/article/item/how_grateful_are_americans.
- Grant, Adam, and Francesca Gino. “A Little Thanks Goes a Long Way: Explaining Why Gratitude Expressions Motivate Prosocial Behavior.” A Little Thanks Goes a Long Way: Explaining Why Gratitude Expressions Motivate Prosocial Behavior , U.S. National Library of Medicine’s Journal of Personality and Social Psychology, 2010, pubmed.ncbi.nlm.nih.gov/20515249/
- Soergel, Andrew. 1 In 3 Workers Employed in Gig Economy, But Not All By Choice, U.S. News & World Report, 11 Oct. 2016, www.usnews.com/news/articles/2016-10-11/1-in-3-workers-employed-in-gig-economy-but-not-all-by-choice.
- Weed, Julie. “These Apps Are an Uber Driver’s Co-Pilot.” The New York Times, The New York Times, 17 Oct. 2019, www.nytimes.com/2019/10/17/business/apps-uber-lyft-drivers.html.
