Establishing & designing threaded mobility service focusing on ethical service for both customers and drivers
A customer- and driver-friendly alternative to Uber & Lyft, prioritizing fair wages, sustainability, safety, and seamless user experience.
Role
UX Designer
Duration
Jan 2025 - May 2025
Industry
Ride Sharing
Team
4 UX Designers
Tools
Figma, ChatGPT, FigJam, Miro, Figma Slides
Design Brief
NextGen Mobility is an innovative ride-sharing service designed to compete directly with Uber and Lyft by offering a more ethical, driver-centric, and customer-friendly experience. With $125 million in funding, the goal is to build a cutting-edge mobility platform that prioritizes fair wages, sustainability, safety, and seamless user experience.
Approach
We treated this as if a startup was launching from zero → designing not only user flows but also the business foundations.
Research
To understand the industry better for consumers, we started by conducting primary and secondary research.
Primary research
We surveyed 55 riders (18+, regular ride-share users) and interviewed 6 to explore their experiences and decision drivers. We got the following insights:
Price determines ride selection & choice of application
Convenient booking, accurate wait times, and a smooth app improve satisfaction
Safety matters—live tracking, background checks, and ride-sharing options create trust
21% audience had an unsafe experience
Consumers switch platforms to get better prices, quality, or safety
Eco-friendly options appeal, but must stay affordable.
Market Research (Desk/Secondary Research)
We conducted competitive analysis and SWOT analysis with our direct competitors Uber and Lyft and indirect competitors Zoox, Waymo, and Zipcar. We found what they did best and where they lacked. To understand the market space and business opportunity, we closely studied the offerings and advantages in the space.
North Star Vision
Based on the research, we formed a north star vision/mission statement as our guiding light throughout the process. Following is our vision and the core principles behind the vision.
Budgeting
We had to divide our budget for the 3 launch phases. We came up with the following breakdown:
Define
Based on the research, we decided to place NextGen as Micromobility, Ride Sharing, and Fleet Partners (Ride coordinators and fleet operators) as a service and as well as in the Magic Quadrant. We place ourselves with the niche players and plan to improve our services to land in the leaders quadrant.
We found that our competitors lack in being fair to driver in terms customer support and wages, they price surge more of ten than required, minimum carpooling options and have long pickup times. So we decided to offer the below offerings as shown in the image in addition to the weakness of the competitors.
Personas
Based on the research, we built 3 consumer personas and 3 service provider personas. For Consumers, we had:
Efficiency Seeker
Pain point: Quick & safe rides during rush hours
Eco-conscious
Pain point: Accessible & Sustainable options
Budget-conscious
Pain point: Affordable options & Rebooking with drivers
For Service Providers, we had:
Driver
Pain point: Fair wage & customer support
Customer support
Pain point: Fair rider-driver dispute resolution & managing high volume of complaints
Stakeholder (Operations Manager)
Pain point: Optimizing operations workflow
KPIs
Ideate
We ideated around certain ideas and decided that NextGen Mobility will have the following offerings. In addition to the following, we have ensured that our community (both riders and drivers) stays safe and is informed about everything.
To ensure that the business lines are consistent and work cohesively, we built a service ecosystem and service blueprint as shown below:
We defined Jobs to be done for each actor in the system:
Service Design Concept
We roughly sketched out the service design concept on how the flow would be, as shown below:
Design
Conceptual Model
To ensure that we are building the right thing, we followed Rosenberg’s Conceptual Model Approach and came up with the Object-Action Matrix, the Attributes Table, and the Prioritization Matrix.
User flow
We then built out the user flow
Design Scope
We built the design scope for rider.
Hardware Touchpoints
Since we are starting from absolute zero, we had to decide on branding, the vehicles we are going to use, and other facilities for our riders as well as driver. For our branding, we went ahead with dark blue since it is associated with safety, trust, and reliability. Given the timeframe, we generated our touchpoints and vehicles using the AI.
Mid-fidelity & High-fidelity Designs
We built the mid-fidelity designs and conducted usability testing on them. Based on the tests, we made the improvements and incorporated them into our high-fidelity prototype. Below are some of the key flows.
AI Preference & Safety
We take input from the users so that our AI can learn based on the users' preferences and behavior.
The ride options shown are based on our AI preferences and learnings.
If the user feels unsafe, they can hit the SOS button, which sends the information packet containing location, rider, and driver details to the police and admin team and informs the emergency contact of the user that something is wrong.
We also show that the police are on their way, so that the user is informed of each step.
Threaded Mobility
We know that there might be a high traffic situation and rides take a huge time.
To solve this issue, we came up with threaded mobility.
Whenever there is traffic, the rider can choose to be dropped at the nearest bike/scooter station by reserving bike/scooter ahead of time to complete the ride.
The driver will be informed and will drop the rider at the nearest bike/scooter station.
Micromobility (E-bikes & E-scooters)
Since we are building sustainable business, we provide our customers with micromobility options: E-bike and E-scooters.
Riders can reserve the E-bike/E-scooter and can unlock them at the selected station.
The rider can drop the vehicle at the nearest hub where our team will go and pick the vehicle from.
Carpooling & Scheduling Ahead of Time
We provide our customers with carpool option and scheduling in advance for their trip.
Once they request the ride, they are notified by the app with the trip details.
In case, if the rider is at the same location for unusual time, we enquire whether they are safe or not.
Testing
We conducted 3 rounds of usability testing. We tested on Mid-fidelity prototype and then with high-fidelity prototype. The usability testing was done as described below. The high-fidelity design was re-iterated upon after the feedback.
The Setup
Participants performed the usability test on Figma’s mobile prototype.
The camera recorded the participant’s reactions
Zoom was used to capture the screens and record the session.
The interviewer noted down the data in the data log.
Quantitative Insights
Tested with 5 participants with a 100% task completion rate.
Satisfaction for tasks: 4.8/5
Confidence for tasks: 5/5
Errors: 0%
Help required: 5% (2 participants needed help because they missed the SOS button)
Qualitative Insights
Expectation on ETA to be visible on the map.
For notification pop-ups, prefer not to read secondary text. So mention important things in titles.
Would like to see ETA for police during an unsafe situation after hitting SOS.
Would like to see the closest micromobility station.
AR Navigation was new but intuitive once users started to use it.
Overall impression of the app: Modern, clean, and safety-focused. Participants mentioned that they felt the company values our time and safety.
Reflections
This was one of the biggest projects that I have worked on. I learned how the smallest details matter to the company’s identity. Since I am not from a business major, doing this project gave me a look into the world of startups and entrepreneurial decisions. Also, delivering within the deadlines and going back and forth absolutely challenged and solved the process at the same time.