Jaime Fowler
Case Study
Destify Online Travel Booking
Role: Product Designer
Team: v0 AI-prototyping
2025-2026
Goal:
Reduce friction and drop-off in current online room booking platform by improving clarity, trust, and decision confidence.
Research:
UX research showed that users were not abandoning the checkout flow because they didn’t want to book but because they lacked confidence at key decision points.
Key insights:
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Users frequently lacked context about why they were in the booking flow and what they were booking
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Room selection caused the highest drop-off due to unclear differentiation between options
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Users left the experience to visit resort websites for clarity and often did not return
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High-stakes decisions were clustered too late in the flow, increasing decision fatigue
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Dense layouts and policy-heavy screens created friction at moments requiring trust
Re-architecturing the user experience from the ground up
Rather than treating the problem as a UI refresh, the solution focused on restructuring the experience to better match user expectations and mental models.
Key changes included:
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Introducing context earlier in the flow to reduce uncertainty
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Reordering steps so users understand what they’re buying before being asked for personal details
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Breaking large decision moments into smaller, more manageable steps
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Aligning layouts and interactions with familiar travel booking patterns
Entry Point: Establishing Context & Trust
Decision: Add clear destination context, wedding details, and visual trust cues on the first screen.
Why: Users arriving via shared links often didn’t know whose wedding they were booking for or where the trip was taking place. This lack of context contributed to early abandonment.
Impact: Reduced ambiguity and allowed users to confidently move forward with minimal interaction using smart defaults.
Room Selection: Supporting Comparison
Decision: Redesign room selection with scannable room cards, clearer bed-type labeling, richer imagery, and filtering/sorting tools.
Why: Users struggled to compare rooms and frequently left the site to understand options elsewhere.
Impact: Lowered cognitive effort by surfacing key differences directly and supporting fast, confident decision-making.
Flow Change: Transportation Before Traveler Details
Decision: Move transportation selection ahead of traveler details to support bundled packages and delay personal data entry.
Why: Asking for personal information too early created friction and drop-off, while transportation decisions felt more natural immediately after room selection.
Impact: Created a clearer purchase narrative and supported future flight + hotel bundling.
Checkout & Payment: Reducing Decision Overload
Decision: Use progressive disclosure, add cost transparency, and remove optional services from the primary path.
Why: Users were overwhelmed by too many high-stakes decisions at once, especially without clear explanations.
Impact: Improved clarity at the moment of purchase and reduced hesitation tied to uncertainty.
Business & UX Outcomes:
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Addressed the highest drop-off points in the booking journey
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Reduced unnecessary friction and backtracking
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Improved alignment between user expectations and system behavior
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Created a scalable foundation for future features, including AI-powered travel bundling
Target outcome: Increase end-to-end booking completion from under 7% to 10%+ through improved confidence and clarity.
Conclusion:
This project demonstrates how research-driven UX decisions, focused on context, pacing, and trust—can meaningfully impact conversion without increasing complexity. By designing for how users think rather than forcing them through rigid flows, the experience becomes more intuitive, more supportive, and more effective.
This prototype is currently being implemented by our development team with an expected go-live date in March 2026. This case study will be updated to include real metrics and initial outcomes once the new booking experience has been launched to our initial user group.