Jeury Santos-Portfolio

Project:

The Pick Ride-Sharing App was designed to provide an affordable and user-friendly ride-sharing service, particularly aimed at commuters and group riders in Latin America. As the Lead Product Designer, my role was to address the pain points associated with ride-sharing, especially focusing on affordability, efficiency, and trust. This case study explores how I led the team in identifying user needs, designing a seamless experience, and delivering an innovative solution

Problem Statement:

The ride-sharing industry, particularly in Latin America, suffers from a significant pain point: affordability. Many users find existing services like Uber and Lyft too expensive, which limits their access to reliable transportation. Additionally, users expressed dissatisfaction with long wait times and a lack of trust in the drivers' reliability.

Key Challenges:

Affordability: Ride-sharing costs were prohibitively high, especially for everyday commuters and group riders.

Trust & Transparency: Users lacked trust in drivers and the fare system, often questioning if they were getting a fair price.

Efficiency: Long wait times frustrated users who needed more reliable ride options, particularly for urgent or group travel.

Affordability: Ride-sharing costs were prohibitively high, especially for everyday commuters and group riders.

Trust & Transparency: Users lacked trust in drivers and the fare system, often questioning if they were getting a fair price.

Efficiency: Long wait times frustrated users who needed more reliable ride options, particularly for urgent or group travel.

Affordability: Ride-sharing costs were prohibitively high, especially for everyday commuters and group riders.

Trust & Transparency: Users lacked trust in drivers and the fare system, often questioning if they were getting a fair price.

Efficiency: Long wait times frustrated users who needed more reliable ride options, particularly for urgent or group travel.

Goals & Objectives:

Improve Affordability: Create a more cost-effective ride-sharing model for users, particularly in regions where cost is a significant barrier.

Increase Trust: Enhance the trust and transparency between riders and drivers through better communication and visible ride options.

Enhance Efficiency: Offer quicker, more predictable rides, even for users in a hurry.

Improve Affordability: Create a more cost-effective ride-sharing model for users, particularly in regions where cost is a significant barrier.

Increase Trust: Enhance the trust and transparency between riders and drivers through better communication and visible ride options.

Enhance Efficiency: Offer quicker, more predictable rides, even for users in a hurry.

Improve Affordability: Create a more cost-effective ride-sharing model for users, particularly in regions where cost is a significant barrier.

Increase Trust: Enhance the trust and transparency between riders and drivers through better communication and visible ride options.

Enhance Efficiency: Offer quicker, more predictable rides, even for users in a hurry.

I conducted surveys, interviews, and competitive analysis to identify user pain points and better define our target group: daily commuters in Latin America. These insights revealed issues like unclear pricing and slow ride-matching, which shaped my early hypothesis. This research not only confirmed the problem but also guided the development of features like dynamic pricing and the "Pick Now" option, addressing both cost concerns and efficiency.

I conducted surveys, interviews, and competitive analysis to identify user pain points and better define our target group.

As the Lead Product Designer, I worked closely with the engineering team to ensure the product's feasibility. Given the complexity of real-time bidding and the integration of dynamic pricing algorithms, constant communication was key. We used Agile methodology, allowing for iterative feedback and quick changes to be made throughout the development process.

Collaborations

We analyzed key competitors like Uber, DiDi, and Lyft to identify gaps and opportunities for Pick to stand out.

Maket Research

Surveys were distributed to a broader audience to validate initial findings and understand how ride-sharing services impact users' daily lives.

Survey

Flied Observation

It was crucial to identify user pain points beyond verbal communication, so I decided to conduct in-field observations to collect notes. These insights allowed me to distinguish between the wants and needs of the users. It provided an opportunity to identify major competitive pitfalls, which became key focus points for delivering enhanced design solutions to the users and adding value to the business.

Users wanted more control over pricing, with many expressing interest in a bidding or dynamic pricing model to reduce costs.

Users valued transparency regarding driver location, ride time, and pricing. A clear, upfront system was necessary to gain user trust.

Users were willing to pay slightly more if it meant significantly reducing wait times.

After completing our primary and secondary research, I collaborated with senior stakeholders to define user personas, focusing on their goals and pain points. Instead of creating traditional, specific personas, I opted to develop user groups, which allowed us to represent a broader user base. This approach enabled us to capture a more diverse range of needs and behaviors, ensuring that our product would cater to a wider audience.

I initiated the ideation process by hosting a discovery workshop with key stakeholders to refine user pain points and align on feature development. We brainstormed concepts like transparent pricing and real-time bidding, which led to features like the 'Pick Now' option and dynamic pricing, giving users more control over their ride costs.

After sketching out initial ideas, I created wireframes and developed an information architecture that outlined user flows. Leveraging a design system, I delivered a high-fidelity prototype, ensuring consistency and scalability across the app.

I initiated the ideation process by hosting a discovery workshop with key stakeholders to refine user pain points and align on feature development. We brainstormed concepts like transparent pricing and real-time bidding, which led to features like the 'Pick Now' option and dynamic pricing, giving users more control over their ride costs.

After sketching out initial ideas, I created wireframes and developed an information architecture that outlined user flows. Leveraging a design system, I delivered a high-fidelity prototype, ensuring consistency and scalability across the app.

I initiated the ideation process by hosting a discovery workshop with key stakeholders to refine user pain points and align on feature development.

I conducted a discovery workshop with a cross-functional team, including engineering, marketing, and business stakeholders, to align on the user insights and potential solutions.

Discovery Workshop

I focused on creating a clear and intuitive information architecture (IA) to streamline the user experience. I began by mapping out the user flows, identifying the key interactions users would have with the app—such as ride booking, bidding, and payment options.

Information Architecture

In the wireframing phase, I translated the ideas from the discovery workshop and information architecture into low-fidelity wireframes using Figma. The wireframes focused on key features such as ride selection, dynamic pricing, and the 'Pick Now' bidding system. My goal was to ensure clarity and ease of use, providing a foundation for testing interactions and navigation.

Design System

Once the wireframes were validated through feedback, I developed high-fidelity prototypes using our established design system to ensure visual consistency across the app. These prototypes incorporated real data, polished visuals, and interactive elements, showcasing the core features like dynamic pricing, driver profiles, and the 'Pick Now' option