Revenue Management +
How might we guide and empower junior RM analysts with an intuitive onboarding experience to help them identify markets to work on and take action.
Role
UX Design Intern
Team
2 PMs
1 Developers
1 Researcher
1 UX Strategist
Time
10 weeks
Skills
User Research
User Personas
Prototyping
AI Design
Tools
UserTesting
Figma
Figjam
Figma Make
What is Revenue Management?
PROS Revenue Management (RM) helps airlines set and adjust fares to maximize revenue. It supports analysts with tools to forecast demand, manage pricing, and respond to market changes quickly and effectively.
Challenge
Research indicates that the current login experience can feel disorienting. Analysts are often dropped into a specific market view without context or guidance, making it difficult to understand where to focus. Many users also find performance charts hard to interpret, which can limit their ability to take confident, informed action.
Overall, users lack a clear and intuitive entry point. They’re unsure which markets to prioritize or what steps to take next, and existing visualizations don’t always surface insights in a way that supports quick decision-making.
Why It Matters
Impact on Revenue:
Analysts struggle to identify priorities, which can delay or misguide pricing decisions.
Lack of in-app guidance leads to missed opportunities to optimize fares and manage markets effectively.
Impact on Customer Experience
New and inexperienced analysts feel unsupported, leading to frustration and reduced confidence.
Confusing visualizations and unclear workflows increase reliance on external tools, weakening engagement with RM.
Impact on Product Adoption
Usability gaps and lack of training support contribute to lower adoption and underutilization of RM’s core features.
Overview of Solution
Internship is ongoing! The full solution will be available mid-August
Research & Discovery
As a UX intern, I joined the project after the research phase. My role was to synthesize these findings—connecting patterns across surveys, focus groups, and internal assessments—and translate them into actionable design insights.
Research Insight: 53% of end users surveyed have less than 5 years of experience using RM. With 38% having less than 2 years experience.
Key Finding: Analysts Are New & Inexperienced
A large portion of RM users are early in their careers, which makes intuitive design and in-product guidance especially critical.
Research Insight: Only 28% of end users surveyed receive training on a 1 to 6 basis routinely
Key Finding: Gaps in Training & Support
Without regular training, users often struggle to fully leverage RM’s capabilities, especially as the product evolves.
Key Finding: Overreliance on External Tools
Many users turn to third-party tools for reporting and analytics—functions that RM already offers. This signals a gap in discoverability or usability.
User Personas
Building on the research, I created user personas that capture the key behaviors and needs of RM users: Junior Analysts, Experienced Analysts, and AI Agent.
Check them out below!
Notable Mention
I created the company’s first AI agent persona, expanding our design approach to consider intelligent system roles and collaborative workflows.
Design Process
Understanding our users helped clarify where the design could make the most impact. I mapped out a workflow to guide users through key tasks with more clarity and confidence.
01
Lo-fidelity Wireframes
To support junior analysts who often felt overwhelmed at login, I contributed to early wireframes that restructured the RM app’s landing experience for clarity and ease of use.
Reorganized content to reduce cognitive load and improve scannability
Focused on guiding users toward high-priority markets and next steps
Collaborated with PMs, developers, and stakeholders in early alignment sessions
FigmaMake Iterations
I co-led the transition from wireframes to high-fidelity designs in Figma.
Designed UI components like market cards, severity badges, and layout structure
Refined visual hierarchy to support quick scanning and decision-making
Ensured the interface felt approachable and intuitive for newer users
02
03
My Markets
This redesigned landing page was created to give analysts a clear, personalized starting point.
Designed a dashboard view of assigned markets with severity indicators and key metrics
Helped define how the AI chatbot integrates into each market card for contextual support
Market Overview
To help analysts—especially newer ones—interpret data more confidently, I contributed to the redesign of the Market Overview page and supported the integration of the AI assistant.
Highlighted key metrics like revenue, load factor, and forecast accuracy
Helped shape the AI chatbot side panel, which offers plain-language explanations and suggested actions
04
05
AI-First Design Exploration
We explored an alternative version of the RM experience that starts with the AI assistant—not a dashboard. This direction was inspired by research showing that junior analysts often don’t know where to begin.
Project is ongoing - will be complete by Mid-August
Check out more of my case studies
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