Gen AI – Your Concierge for Hotel Discoverability
To anyone who travels regularly, one thing is clear: The process of booking and planning a trip has become more complicated as travel-related digital platforms have proliferated. That includes the process of evaluating lodging. But now, we’re poised to see another evolution in the way we all make our travel decisions. And you guessed it – that evolution is coming from AI, specifically in how AI search streamlines the decision-making process.
Until quite recently, travelers have relied on manual, detail-heavy methods to find hotels. They would start with the locations they planned to visit, plus the amenities and other features they required. Then they’d turn to the myriad self-serve platforms at their fingertips. Google, TripAdvisor, Expedia, Orbitz and so many others turn up a mountain of search results to parse. Platforms like AirBnB or VRBO present travelers with entirely new categories of lodging to consider, with differentiating features like trust signals and highly detailed reviews that make it hard for hotels to compete.
All the options muddle the process of hotel selection and lead to browsing fatigue. Travelers today are hungry for a solution that can do the searching and summarizing of options for them. That’s exactly what AI platforms like ChatGPT and Perplexity are starting to do today. They’re enabling consumers to skip the scroll and see a hotel’s pros and cons in an easy-to-understand answer to a query.
AI search raises the bar for aggregating and verifying business information
Hotel selection used to mean juggling multiple browser tabs and periodically checking for prices to drop. Now AI search tools are baked directly into browsers themselves. At the same time, generative AI search is fundamentally changing how search discoverability works for businesses. If consumers trust that AI search results will be authoritative, businesses will need to make sure their own information is up to date and accurate in the sources AI uses. A hotel choice made with faulty information can make for a bad trip – and a negative association with the hotel’s brand. Now is the time for hotels, especially franchised or multi-location hotels where the problem is complex, to prepare their data to deliver relevant, accurate, useful AI search results for in-market travelers. Hotels will need to be able to unify their data in one place, to more efficiently verify it delivers consistent, on-brand information across all locations as well as accurate location-specific information.
If a hotel business has its public data in good order, it’ll be in a prime position to take advantage of hotels’ competitive edge in the marketplace. Let’s remember: AirBnBs and the like have novelty on their side, but hotels have consistency on theirs. No two AirBnB hosts offer quite the same experience – and that makes finding an AirBnB with the right idiosyncrasies exhausting. With cleaning fees and other surcharges pushing up nightly rates – and with local regulations in many popular destinations creating scarcity – travelers simply have less of an expectation that AirBnB will deliver a budget advantage. It’s harder to justify the information overload that comes with selecting accommodations.
Hotels can lean into their data advantage – if they’re prepared
Hotels have the advantage of being able to offer a consistent guest experience at every location. Each location needs to be on-brand, and to adhere to a consistent set of policies. Consistency is, fundamentally, a key reason why multi-location hotels came to prominence in the market in the first place. To lean into this advantage, hotels must manage and syndicate their data to suit the way travelers browse for lodging today. Unifying data across all locations enables a multi-location hotel business to cater to search engines, and to control the information generated by AI search tools.
The competitive advantage of hotels in search will rest on discoverability and the reliability of AI search summaries. This can easily become an arduous, manual task for local managers and franchisees as well as the business’s central headquarters. The task is to maintain search and social profiles for location-specific accuracy and on-brand messaging. Hotels need a more efficient method, one that breaks down data silos inside the organization and maintains consistent, accurate data in all digital channels. Aggregating data for more efficient syndication is a crucial step in the path toward delivering clarity, accuracy, relevance, and personalized messaging to hotel customers via AI search. Furthermore, a unified data framework enables a hotel business to use AI to automate the cross-platform data-gathering process to optimize their digital presence over time.
To win in AI search, get to unifying and verifying the data
Travelers booking hotels today deserve efficiency wherever they can get it – and with AI search on the scene, they’re coming to expect efficiency at new levels. Multi-location hotel businesses need to rise to the occasion by aggregating information at the location level, so these details can be verified and delivered to search engines in the form of detailed online profiles and landing pages.
Hotels face two key challenges today: ensuring data accuracy across platforms and using AI search to present data effectively. It’s no longer enough to be listed on booking sites – hotels must manage their digital profiles in a unified way. This improves search performance and ensures AI tools will provide reliable, up-to-date information.
Because AI relies on large amounts of data from disparate sources, hotels with strong digital infrastructure will thrive. Unified data ensures AI-generated search results will be accurate and helpful, creating a seamless experience for travelers. The future of hotel marketing depends on how well hotels manage their data. Mastering AI search is essential for hotels to stay competitive and deliver seamless, satisfying experiences.