Methods used

• Reviewed app store reviews to identify recurring complaints and usability frustrations directly from users.
• Analyzed support tickets to uncover technical issues, common feature requests, and problem areas that blocked task completion.
• Conducted a hands-on audit of the app’s UI and UX to pinpoint inconsistencies, accessibility barriers, and confusing workflows.
• Completed a competitor analysis for chatbot design using FigJam, comparing features, layouts, and user flows across popular AI tools.

Key findings from app audit

• Visual inconsistencies: Icons were not standardized across screens, leading to user confusion.
• UI alignment issues: Text and UI elements were misaligned, making the interface feel less polished and harder to scan.
• Poor image quality: Blurry images undermined trust in the app’s professionalism.
• Accessibility concerns: White text on a gray background reduced legibility; other screens also lacked sufficient color contrast.
• App logic gaps: Copy like “be first to comment” appeared even when comments were already posted.
• Usability gaps: No option to reply to comments, and sections could only be closed by swiping instead of having a clear “X” button.
• Notifications bug: Users received notifications even when the feature was turned off, creating frustration.
• App stability: Certain actions and button clicks caused the app to crash, directly impacting trust and usability.

Insights for payouts tab

• Navigation issue: Payouts were buried within the settings menu, even though they are a primary motivator for users.
• Recommendation: Relocate payouts to a dedicated tab in the bottom navigation bar for immediate access.
• Motivational design: Highlight both “total earnings” and “potential earnings” from ongoing claims to encourage users to complete processes and feel rewarded for past settlements.

Insights for chatbot

• Competitor benchmarking: Studied AI chatbots including ChatGPT to analyze tone, usability, and layout patterns.
• Effective features noted: Search suggestions, conversational prompts, and clear legal disclaimers to set expectations.
• Pitfalls to avoid: Overly technical responses, cluttered layouts, and lack of context retention that can reduce clarity and trust.

A look into our FigJam competitor analysis of currently available AI search tools, chat bots, search suggestions, and our client's current search screen

Ideation 

• Began with competitor analysis on FigJam, mapping common chatbot flows and identifying features that worked well.
• Sketched initial chatbot layouts and app redesign concepts on paper to brainstorm freely without digital constraints.
• Translated sketches into low-fidelity wireframes in Figma to visualize structure and flow.
• Iterated on multiple variations of chatbot and payouts screens to give the client a range of options.

Our ideation process allowed rapid exploration of layouts and flows without digital constraints and progressive refining based on team and client feedback. Doing so ensured the client had multiple design options to review and approve. 

AI Use

In addition to traditional UX ideation methods, I explored AI tools to support the creative process for the payouts tab. Using ChatGPT and Google Stitch AI, I generated early concepts aligned with the client's intended direction and screen structure. While these outputs provided inspiration, they lacked the level of polish and usability required. I selectively drew on useful ideas from the AI results, then designed the final payouts tab from scratch in Figma, ensuring the solution was both user-centered and aligned with project goals. 

Collaboration

• I worked in a small design team where feedback was continuously exchanged on drafts and iterations.
• Shared progress with the client at key checkpoints, incorporating feedback directly as the client had final approval on all design decisions.
• Acted as the sole designer in the second phase of the project, managing both creative direction and execution.

Constraints

Like many other real-world projects, Suits faced limitations that shaped the design approach. 

• Time limitations: Limited weekly collaboration (one or two hours per week) required efficient, focused design sessions. 
• Client direction: A close resemblance to ChatGPT balanced client expectations with innovation. 
• Technical feasibility: Trade-offs such as omitting persistent chat history ensured the product remained practical to build.

Chatbot Feature 

The chatbot was designed to help users answer both general settlement FAQs and case-specific questions. My client requested that the experience resemble ChatGPT, which guided much of the layout and interaction model. 

By reframing payouts as both a functional tracker and a motivational tool, the redesign made the feature more intuitive and rewarding, helping users stay engaged throughout their settlement journey.

Suggest Tab Redesign

The Suggest tab was underutilized due to extra steps, unclear input fields, and accessibility limitations. The redesign prioritized streamlining actions, improving clarity, and driving user engagement. Since the updates built on existing high-fidelity Figma designs, I focused on refining and modifying those screens directly rather than beginning with low-fidelity wireframes.

Validation Methods

• Stakeholder feedback on wireframes: Collected early reactions to low-fidelity wireframes to confirm direction before investing in detailed design.

• Design critiques: Shared high-fidelity screens with design leads across multiple teams to gather expert feedback.

• Iterative refinements: Incorporated suggestions and re-presented updated designs to stakeholders for final validation.

Feedback received

• Visual hierarchy: Suggested using italics for claim tiles to improve clarity.

• Readability: Recommended adding more space between info boxes and headers for clearer readability.

• Brand consistency: Requested switching screen background with a blue gradient instead of yellow for a more modern look.

• Layout balance: Noted the need to extend gradients higher on screens for better visual proportion. 

• Polish: Asked for consistent margin alignment across elements.

What I learned

• Presenting multiple variations helps stakeholders make faster, clearer decisions.

• Live revisions during feedback sessions can accelerate iteration and reduce back-and-forth.

• Small visual adjustments, such as spacing, typography, and alignment, can significantly impact usability and perceived quality.

• Stakeholders often respond well to options framed in terms of why they improve clarity or aesthetics, not just what was changed.

• Iterative critique from both peers and stakeholders ensures designs are not only functional but also visually cohesive and aligned with brand expectations.