Akoya Travel
AI-Powered Travel Planning Platform
TL;DR What did I do?
Led comprehensive redesign of AI-powered travel planning platform as sole designer, reducing task error rates by 13.9% and increasing user satisfaction by 19% through systematic usability testing and strategic information architecture improvements. A research-driven redesign that transformed overwhelming travel planning into intuitive user experiences by advocating for comprehensive testing, streamlining cognitive load, and establishing scalable design frameworks. →Strategic user testing methodology across diverse demographics →Information architecture redesign reducing cognitive overload →Systematic input optimization from complex forms to essential interactions →Framework development for AI-human collaboration patterns
The Challenge
The Client's Assumption
Akoya Travel approached me believing their AI-powered platform just needed polish. They had built a system promising users could "plan and book trips within a single screen" and felt confident the AI capabilities were solving travel planning complexity.
However, I suspected there were deeper usability issues. While the client focused on showcasing AI features, I noticed potential problems with information architecture and user cognitive load that could be undermining the entire experience.
Reframing the Problem
Rather than accepting the client's assumption that minor tweaks would suffice, I advocated for a research-first approach to understand what was actually happening with users.
I told the client: "Before we start redesigning based on assumptions, we need systematic data about how users actually interact with this platform. Let me identify where the real friction points are."
The Real Challenge Revealed
My heuristic analysis revealed the core issue wasn't about AI capabilities but about information presentation and user cognitive burden. The platform suffered from information overload and lack of clear hierarchy, making navigation difficult despite powerful underlying technology.
I reframed the challenge: "How might we leverage AI capabilities while reducing cognitive load, so users can focus on travel decisions rather than fighting the interface?"
This strategic reframing shifted the project from feature polish to fundamental user experience optimization.
Systematic Research & Testing Strategy
Advocating for Comprehensive Testing
When the client was ready to jump into redesigns, I pushed for extensive user research to validate our assumptions and uncover problems we couldn't see from internal perspectives.
I designed a comprehensive testing strategy with 15 usability tests across two distinct demographic groups: retirees (50+) and Gen Z/Millennials (18-30). This wasn't just about gathering feedback but about understanding how different user mental models approached travel planning.
Strategic Testing Methodology
I developed a systematic approach that went beyond basic usability testing:
Hypothesis-Driven Framework: I formulated specific hypotheses before testing, ensuring we had quantifiable success criteria rather than subjective feedback.
Demographic-Based Insights: By dividing testing across age groups, I could identify whether usability issues were universal or specific to different user types and technical comfort levels.
Multi-Modal Data Collection: I established both quantitative metrics (error rates, completion times, NPS) and qualitative observation protocols to capture the full user experience story.
Testing Results & Strategic Insights
The results validated my concerns about information architecture:
15% task error rate suggested interface confusion
72% NPS was good but indicated room for improvement
Qualitative feedback consistently mentioned feeling "overwhelmed" by information density
Most importantly, I identified that users weren't struggling with AI concepts but with how information was organized and presented to them.
Strategic Design Solutions & Leadership
Design Principles Framework
Before diving into redesigns, I established three strategic principles that would guide all design decisions:
Simplicity & Clarity: Reduce mental effort through straightforward language and clear visual hierarchy Contextual Personalization: Use AI strategically to match user interests without overwhelming choice Visual Engagement: Create immersive experiences that inspire rather than intimidate
Input Optimization Strategy
The Problem I Identified: The original flow required 7 essential input fields before users could see any recommendations. User feedback revealed this felt like "too many unnecessary questions" that made "trip planning with AI less appealing."
My Strategic Solution: I applied the Principle of Least Effort, reducing inputs from 7 fields to 3 essential ones: location, travel preferences, and additional notes. I eliminated email and budget requirements while making travelers and dates optional.
This wasn't just about fewer fields but about respecting user mental energy and allowing progressive disclosure of complexity.
Information Architecture Redesign
The Challenge: Users experienced cognitive overload from extensive descriptions and relied on AI chatbox for changes, which wasn't intuitive for travel planning tasks.
My Framework: I redesigned the information architecture based on real-world systems and cognitive load principles:
Spatial Reorganization: I transitioned the day-by-day display from vertical to horizontal format, improving information hierarchy and reducing unnecessary mouse movements.
Content Optimization: I restructured detailed descriptions into concise bullet points, reducing cognitive processing while maintaining necessary information.
Progressive Disclosure: I added detailed pop-up views for location images, providing depth when users wanted it without cluttering the primary interface.
User Control & Freedom Framework
Following usability heuristics, I designed comprehensive user control systems:
Edit View Innovation: I created intuitive editing capabilities allowing users to delete, regenerate, or add itinerary items without starting over.
Familiar Navigation Patterns: I maintained the left navigation bar structure (inspired by successful patterns like ChatGPT) for seamless trip management and modification.
This approach balanced AI automation with user agency, ensuring people felt in control of their travel planning process.
Strategic Feature Development
Based on testing insights, I designed features that addressed real user needs:
Collaboration Tools: Share functionality and calendar integration addressing the collaborative nature of travel planning Consolidated Management: Bookings/attachments section and budgeting tools reducing platform switching Contextual Visualization: Map view providing spatial context that matched how users naturally think about travel
Brand Strategy Leadership
I identified that the original pink and azure color scheme was undermining the platform's credibility with users. The gradient backgrounds created readability issues that were hurting usability.
I developed a strategic color palette of beige, charcoal black, and midnight blue that conveyed elegance and sophistication while improving functional usability. This became the foundation for all subsequent design work.
Measurable Impact & Framework Creation
Quantified Transformation
My systematic approach delivered significant measurable improvements:
13.9% reduction in task error rates - Better information architecture reduced user mistakes
19% increase in user satisfaction - Strategic simplification created more confident, happy users
Maintained 100% task completion across diverse demographic groups
Strategic Frameworks Established
Beyond immediate metrics, I created several frameworks that transformed how Akoya approaches travel UX:
The Demographic Testing Framework: Systematic methodology for gathering diverse user perspectives across different user mental models and technical comfort levels.
The Cognitive Load Optimization System: Principles for reducing extraneous cognitive burden while maintaining functionality in complex planning interfaces.
The Progressive Input Methodology: Approach to streamlining user onboarding without sacrificing personalization capabilities.
The AI-Human Collaboration Framework: Design patterns for intuitive AI-assisted decision making that preserves user agency.
Implementation & Delivery
I created over 50 high-fidelity screens covering the complete user journey from onboarding through trip completion. Every screen included comprehensive annotations with exact component dimensions and detailed specifications for seamless developer handoff.
I also established a complete style guide integrating typography, color systems, and component libraries, ensuring design consistency and scalability for future development.
Long-term Strategic Impact
The testing methodology I developed became Akoya's standard approach for validating design decisions. The information architecture principles I established provided a scalable framework for future feature development.
Most importantly, I demonstrated how systematic user research could transform business outcomes, shifting the client's approach from assumption-based design to evidence-driven decision making.
Takeaways
This project reinforced my approach to design leadership: advocate for user research over assumptions, use systematic methodologies to guide strategic decisions, and create frameworks that enable long-term success rather than just immediate fixes.
The measurable improvements in user satisfaction and task success validated that thorough research and strategic information architecture can transform even well-intentioned products. The frameworks I established continue to guide how Akoya approaches complex user experience challenges.
