HopIn

Neighbourhood Carpooling App

Overview

HopIn is a carpooling app that connects neighbors and colleagues, offering an affordable, eco-friendly alternative to commuting alone. By fostering community connections, HopIn reduces travel costs, eases traffic, and promotes sustainability. In this bootcamp project, I led the design process, user research, and prototyping, focusing on building connections and creating a user-friendly platform that helps people thrive together through shared rides.

Role

UX Designer,content strategist.

Goal

The main objective of HopIn was to create a platform that simplifies carpooling for neighbors and colleagues, fostering community connections while reducing commuting costs and environmental impact. Aimed to reduce commuting costs and increase user interactions By Connecting people in the same area, HopIn helps reduce single-occupancy vehicle usage, promoting both community engagement and sustainability.

Tools

Figma, Miro,Maze

During this phase, I conducted 7 interviews over 4 days to understand the commuting habits and pain points of urban carpoolers. The interview script included 32 open-ended questions, focusing on daily routines, safety concerns, and attitudes toward sharing rides with neighbors.

Interview

Objective: Gain insights into user trust in carpooling with neighbors, motivations for ridesharing, and concerns about safety and convenience.
Main Insights: Users valued the ability to connect with trusted neighbors, preferred a simple ride-matching process, and were eager to lower commuting costs through carpooling.
Application: These insights led us to develop key features such as neighborhood-based ride-matching and a community forum where users could interact and build trust before sharing rides.What objectives influenced your questions?

Surveys

We distributed an online survey to community groups and commuter forums, receiving 25 responses within 3 days. The survey helped us identify key challenges and opportunities in carpooling, including trust, cost, and convenience.

Type of Survey: Multiple-choice and ordinal scale questions, aimed at understanding user attitudes toward carpooling. The survey was created and distributed using Google Forms.
Key Findings: Many respondents were hesitant to carpool due to concerns about safety and the inconvenience of coordinating with strangers. However, there was strong interest in community-based carpooling, where users could connect with trusted neighbors.
Application: These insights led to the development of the community feature, enabling users to interact with neighbors, organize rides, and build a network of trusted carpoolers within their local areas.

Personas

To better understand our users' goals, needs, and behaviors, we created four personas representing our key user segments. Based on user interviews and surveys, these personas were continuously refined throughout the project. They helped us reassess our design decisions and stay user-focused during the HopIn platform's development.

What data did we use?

We gathered data from user interviews, surveys, and focus groups, analyzing user behaviors, pain points, and preferences. This helped us capture relevant demographic, psychographic, and behavioral information about our users.

How did personas impact the design?

Personas guided the prioritization of features like safety, ride-matching, and user interface simplicity. They helped us address specific user needs, ensuring a smooth experience for diverse users, from tech-savvy commuters to community-oriented individuals.

When did we use personas?

We referenced personas during ideation, wireframing, prototyping, and user testing stages, ensuring that HopIn’s design remained aligned with real user needs at every step.

Why did we create personas?

We wanted to ensure that HopIn’s design directly addressed user needs and problems. Personas allowed us to empathize with our users and shape features that aligned with their commuting goals, such as cost savings, community engagement, and eco-friendliness.

What did we specify for each persona?

Basic Info: Age, job, location, education, and demographics.
Technology Usage: Tech-savvy, frequent smartphone user, active on social media.
Motivations & Goals: Reducing costs, community connection, eco-consciousness.
Pain Points: Inconsistent service, complicated onboarding, limited features.

User Journey

To ensure a seamless user experience, we crafted a user journey map for key interactions within the HopIn platform. The goal was to identify friction points and optimize the flow for better user engagement.

Path Selection: We chose to map the ride booking and ride-sharing process since these are core functions. This allowed us to focus on areas most crucial to user satisfaction and retention.

Testing and Validation: We used user interviews, real-time testing, and analytics data to validate the mapped journey. Feedback loops from early users helped confirm the map’s accuracy.

Findings from Journey Mapping: The map revealed pain points, such as confusion during ride selection and delays in booking confirmations. Two unnecessary steps were slowing down the process.

Main Pain Points:

Unclear navigation between different ride options.
Delays in matching drivers to riders.
Lack of real-time notifications for ride statuses.
Design Changes: We streamlined the ride booking flow by removing redundant steps and enhancing the matching process with real-time updates. These changes reduced friction and improved conversion rates, ensuring that users could book rides more quickly and confidently.

Customer Journey

I developed a customer journey map for HopIn to understand how users engage with our carpooling app, identify pain points, and uncover opportunities to enhance the user experience.

Link to user journey map

Stages Examined

Awareness – How users initially discover the app.
Consideration – Factors that influence users to decide whether to try the app.
Acquisition – The registration and onboarding process.
Service – User interactions with the app, booking rides, and using the platform.
Loyalty – Building repeat usage and maintaining satisfaction.

Key Findings by Stage

Awareness: Users exploring the app through advertisements, word-of-mouth, or online search.
Consideration: Users weighing the app's features, reviews, and overall appeal before deciding to download.
Acquisition: Registering, setting up an account, and understanding how the service works.
Service: Booking rides, matching with other users, and navigating the app.
Loyalty: Consistent usage, reliability, and interactions that build trust over time.

Pain Points

The mapping revealed several key issues:

Unreliable ride matches and last-minute cancellations led to frustration.
Unclear pricing created hesitation for users during the booking process.
Users felt overwhelmed by the number of steps needed to complete a booking.
Safety concerns and a lack of trust in the system.

Opportunities

Implement more transparent pricing and ensure users are aware of the total cost upfront.
Streamline the booking process to reduce unnecessary steps, making it faster and simpler.
Enhance ride matching algorithms to improve reliability.
Add safety features such as verified profiles, real-time tracking, and detailed reviews to build user trust.

Outcome

A faster checkout process was designed by eliminating two unnecessary steps, which improved conversion rates.
The app now includes an enhanced user onboarding with tutorials and guides to help new users.
Improved notifications and in-app support to resolve issues quickly, contributing to higher user satisfaction and loyalty.

Low Fidelity Wireframes

Started with low-fidelity wireframes based on initial sketches and industry standards to outline the basic structure.

Tool Used

Utilized Figma to create and refine wireframes.

Testing & Feedback:

Conducted 4 user tests on low-fidelity wireframes. Gathered insights and identified necessary changes to enhance user flow and interface clarity.

Iterations

Made a few alterations based on feedback, leading to improved wireframes before progressing to high-fidelity prototypes.

Final Stage

Added relevant stock images and marketing copies, then moved forward with high-fidelity prototypes for final user testing.

Brand Guidelines

Usability testing

I created a fully-functional, high-fidelity prototype of the new flows using Axure. At the same time, we started recruiting subjects for the test who fit our criteria. We did 4 usability tests in the first round and 3 after iterating on the issues that I’ve identified

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