Voyager App

Role

User Research Lead — interviews, qualitative analysis, insight synthesis, and research-backed design recommendations; Wireframing; User Interface Design aid

Period

March - May 2024

Project Overview

Voyager is a concept mobile application for booking bus and train tickets, designed to support frequent (e.g. student) commuters and international travelers. Many existing travel apps require users to switch between multiple platforms, suffer from unclear pricing, and introduce unnecessary friction during the booking process.

This was a group UX project, where I led user research and insight generation, including interview planning, participant recruitment, qualitative coding, and synthesis. The goal was to ground the product decisions in real user behavior and ensure that the final design reflected genuine needs rather than assumptions.

Understanding the Problem

Initial competitor analysis of existing travel apps revealed a pattern of frustration: slow performance, unclear booking steps, price unpredictability, and forced choices that did not match users’ intentions.

Through early research, we identified several key problems:

Users rely on multiple apps depending on route and provider
Booking flows are often longer than necessary
Price changes and add-ons reduce trust
Apps rarely adapt to frequent travelers’ habits

Problem statement:
How might we design a travel app experience that aligns with how users actually search for, compare, and book bus or train tickets?

Research Approach & Insights

I led the user research phase, conducting 10 semi-structured interviews with regular student commuters and international travelers. Open-ended questions were used to gather unbiased insights about travel habits, app usage, frustrations, and desired features. Interviews were recorded with consent and followed a structured interview guide.

My responsibilities included:

Designing interview guides and recruiting participants
Conducting, recording, and transcribing interviews
Coding and synthesizing qualitative data using affinity diagramming with a part of the coding process illustrated below as an example
Supporting insights with light quantitative analysis

Key insights included:

All participants use multiple travel apps.
Users begin with location → destination → time → price
Speed and clarity matter more than visuals
Nearest stop detection matters to users.
Price transparency directly affects trust (talking about "hidden" prices in later booking stages)
Saving routes and personal data reduces friction
Most users did not want plane tickets included

These insights became the foundation for our user personas (one of our personas is a Swedish student - the research was conducted in Sweden, the other is an international), feature prioritization and interaction design.

Responsibilities and going from research to design

Research insights were translated into concrete design decisions through close collaboration with the team.

I contributed by:

Creating low-fidelity wireframes that reflected users’ natural booking flow, some seen below
Helping define the information architecture and sitemap based on realistic user journeys and competitor weaknesses, seen below
Ensuring the booking journey mirrored real user mental models
Aiding in UI design decisions, focusing on clarity, accessibility, and consistency
Supporting the development of a shared design system. The design system uses the Nexa font and a purple-pink-white color palette to evoke clarity, friendliness, and quality. An interactive prototype was built in Figma based on this system.

Key design outcomes

Takeaways for most important solution features:

One app for multiple bus and train companies
Mobile-first, search-focused entry point
Clear step-by-step booking process with fast navigation
Guest checkout and saved routes
Simplified interactions with minimal cognitive load
Nearest stop detection
Cheapest options shown first
No plane ticket integration

You can explore the prototype here:

Mobile prototype

Testing, Iteration & Validation

Usability testing was conducted with 5 participants using task-based scenarios (searching for tickets and opening a booked ticket) and the think-aloud method.

Results showed:

High task success rates
Clear navigation and understandable interactions
Minor visibility issues with one-way/round-trip buttons

Based on findings, we iterated by:

Increasing contrast on key buttons
Adding prices to the calendar view
Displaying trip duration and delay indicators more clearly

These changes reinforced clarity without adding complexity. Official project report screenshots showcasing changes shown below.

Outcomes & Learnings

Although the product was not launched, usability testing validated the research-driven direction: users completed booking tasks successfully and described the experience as clear, intuitive, and efficient.

What I learned:

Strong research leads to clearer design decisions
Clear insight framing makes prioritization easier
Saying “no” to features can be just as important as adding them
Bridging research and design strengthens UX outcomes

This project reinforced my interest in user research and insight-driven design, and strengthened my ability to align design goals with user needs.