AI Booking Assistant is an AI-powered travel booking experience that simplifies trip planning through natural conversation. Instead of navigating complex interfaces, users describe their needs and receive personalized hotel recommendations. The MVP focuses on hotel bookings through a seamless chat-based flow, with a long-term vision to expand into a full travel platform including flights, activities, events, and car rentals.

As the UI/UX designer, I translated a complex booking process into an intuitive, conversational experience.

Key Contributions:

• Conducted user research to uncover pain points in travel planning and AI expectations.
• Performed a competitive analysis of major booking platforms to identify gaps, opportunities, and differentiators for an AI-first experience.
• Defined the product vision and MVP scope using a Lean Canvas.
• Designed the AI-driven booking flow, mapping how the assistant collects user intent through conversation.
• Created clear, minimal UI screens for the hotel-booking MVP.
• Built the booking funnel to visualize user interactions and friction points.
• Ran usability testing, analyzed CSV logs, and identified behavior patterns and drop-offs.
• Summarized findings into actionable insights and recommendations for improving the next iteration.

Context

Travel planning often requires users to switch between multiple apps to compare hotels, flights, and activities, creating a fragmented experience. Our goal was to simplify this process with an AI assistant that helps users plan trips through natural conversation.

Through user research and competitive analysis of AI-assisted travel platforms, we identified key needs: clear guidance, personalization, and seamless support from planning to booking. These insights shaped the scope and priorities of the MVP.

Lean MVP Approach

To achieve this, we focused on creating an efficient, vibe-coded MVP that would reflect the core value of the assistant without a large engineering investment.

We prioritized the essential steps of the hotel-booking flow - ****collecting user intent, generating tailored recommendations, and guiding users through a seamless conversational journey. This allowed us to rapidly prototype, test assumptions early, and refine the assistant’s logic based on real user behavior.