Imagine having hundreds of filters on your platform, but your customers still can't find what they're looking for. That was Booking.com's reality. After a decade of machine learning success, their traditional search was hitting a wall during the crucial "discovery" phase of travel planning.

The platform excelled at the transactional last mile—getting people from search to booking—but struggled with open-ended, thematic queries. As Enggist notes, "We've always been really good at the last mile—getting people from search to booking. But discovery was different. We needed a way to meet customers earlier in the process, when they were still figuring out what they wanted."

Booking.com deployed a five-pronged AI assault on the discovery problem, each solution purpose-built to solve specific customer friction points:

AI Trip Planner

Challenge it solves: Travelers struggle with the overwhelming task of planning trips from scratch, especially when exploring unfamiliar destinations.

How it works: A conversational tool that transforms natural language prompts into destination suggestions and complete itineraries. Think of it as having a travel-savvy friend who never gets tired of your "what if" questions.

Smart Filters

Challenge it solves: Traditional search relied on drop-down menus and checkboxes, limiting travelers to a small number of predefined filters.

How it works: Uses GPT-4o mini to understand natural language prompts like "sunset views" or "great gym." Goes beyond predefined filters by analyzing reviews, images, and listing details. Surfaces more relevant results, driving higher engagement and conversions.

AI Review Summaries

Challenge it solves: Travelers often struggle to sort through thousands of reviews when comparing properties.

How it works:GPT-4o mini analyzes and summarizes reviews into key themes like cleanliness, location, and amenities. Generates short, digestible summaries, reducing time spent comparing properties and increasing booking confidence.

Property Q&A

Challenge it solves: Many travelers have specific questions about properties that aren't easily answered in a static listing.

How it works:OpenAI's LLMs were fine-tuned on Booking.com's user-generated content and property descriptions. Handles queries like "Is there a crib available?" or "Is the pool open in winter?" Adapts to ambiguity, such as different pet policies (what qualifies as a "large dog" varies by property).

Help Me Reply

Challenge it solves: Property partners need to manage guest communications efficiently and improve response times.

How it works: Built using OpenAI's models to generate automated responses and customizable message templates. Partners can set up auto-replies for common questions, ensuring guests receive quick answers. Provides a "reply score" metric to track and improve response rates.

🎬 Watch Booking.com's AI Transformation

See how Booking.com revolutionized travel discovery by integrating OpenAI's GPT-4o mini to create conversational, personalized experiences for millions of travelers.

The magic happens through seamless integration of OpenAI's Large Language Models (including GPT-4o mini) with Booking.com's existing machine learning infrastructure. The system marries structured data (pricing, availability) with unstructured data (reviews, descriptions) to create curated, conversational travel experiences.

The key was leveraging Booking.com's existing APIs and data infrastructure—enabling rapid prototyping and deployment without rebuilding from scratch. OpenAI's models were integrated through these existing APIs, allowing teams to rapidly test and iterate on new features. This created a stronger foundation for future AI development.

The results speak louder than a tourist with a megaphone:

• Increased User Engagement: The AI Trip Planner and Smart Filters keep users on the platform longer while driving higher conversion rates.
• Faster Search & Higher Booking Confidence: AI Review Summaries and Smart Filters have reduced search time and eliminated booking uncertainty.
• Reduced Customer Support Load: Property Q&A delivers instant, accurate answers, slashing support inquiry volume.
• Foundation for Future AI Development: The integrated infrastructure allows rapid testing and rollout of new AI features.

Rapid User Adoption: Customers immediately shifted from simple keywords to detailed, conversational queries. The interface was so intuitive, adoption happened organically.

Leverage What You Have: Integrating advanced AI models into existing APIs and data infrastructure was the secret to rapid iteration and testing.

🐯 Tiger Takeaway:

The takeaway for executives? Don't rebuild your entire tech stack to embrace AI. Find ways to weave advanced models into your existing infrastructure, and watch your customers discover capabilities they didn't even know they wanted.

AI-Powered Newsletter