Travel Data Analytics Tools

Radisson now has 1,000+ hotels inside ChatGPT. IHG Hotels & Resorts is bringing 7,000+ hotels into conversational search. Amazon is opening Alexa+ to travel partners like Priceline. The old journey looked like this: Guest → Google → OTA / hotel website → booking engine → PMS The new journey could look like: Guest → AI agent → hotel / OTA agent → CRS / PMS And this creates three very different futures. AI → Hotel direct ChatGPT discovers the hotel, accesses live availability and sends the guest directly to the brand. In this scenario, AI could actually reduce OTA dependency. AI → OTA → Hotel Alexa+ recommends a hotel through Priceline. Now there really is another layer between the guest and the property. AI → Multiple suppliers This is the most interesting one. Imagine asking: “Find me a beachfront luxury hotel in Phuket under €700 with a kids club and late checkout.” The AI could compare: Marriott direct IHG direct Booking Expedia Priceline Independent hotels Hotels will increasingly need structured content, live rates, inventory, APIs, CRM context and PMS connectivity that machines can use. The next competitive advantage may not be SEO. It may be becoming machine-actionable. For hotels on OPERA Cloud, OHIP and MCP-style integrations suddenly become much more strategic.

Marriott is spending over $1B on infrastructure. That sounds ridiculous until you understand what is happening in travel. AI doesn't browse like Google. It consumes inventory: rates, availability, policies, loyalty benefits, etc. And it can only recommend what it can read and access instantly. Travel executives think AI will create the next winners. I think AI will expose the winners that already exist. When I worked at Booking.com, hotels constantly asked for better rankings and were voluntarily raising their own commissions from 15% to 18–30% just to appear higher. Visibility was everything.  Back then, it didn't matter if their systems supported real-time data. But now it matters. Hotels used to compete for clicks. Soon they'll compete for inclusion in Claude, ChatGPT, and others. That's why Marriott is investing over $1B to make its inventory readable by AI. And Hilton is consolidating guest data into unified profiles. Whoever becomes AI's preferred inventory source captures the booking and the margin. This shift is invisible to travelers but it's happening inside CRS platforms and PMS systems. Hotels stuck on old systems lose by default. They will become increasingly dependent on OTAs that already have AI-ready feeds. The battle in travel right now is over who becomes AI's default source of truth. When AI searches for a hotel in your city tonight, does it find your property or just Booking.com's listing of it? #TravelTech #Hotels #OTA #AI

How to prepare your hotel for the Agentic AI upheaval? I believe priority #1 for independent hoteliers, midsize and smaller hotel brands is to create true two-way APIs among three crucial technology pieces: PMS-CRS-CRM. This is the only way to prepare the property for the agentic AI, expected to take over hotel bookings, guest relationships and personalization over the next years. Where do hoteliers start? Implement a CRM technology to aggregate all of the property’s first-party and zero-party data, which is then cleansed, de-duped, enriched and appended. If you already have CRM in place, consider upgrading to a CDP to empower property operations and deliver above-and-beyond customer service and personalization. First-party data is the customer data (past customers & guests, website users, opt-in email subscribers, lists of corporate travel managers, meeting planners, wedding and event planners, SMERF group leaders the property has been doing business with or at least in communications with, etc.) that comes from the PMS, CRS, WBE, from the property's website, opt-in email sign-ups, even customer lists sitting on laptops of sales and marketing personnel. The CRM (and CDP for more complex independents, midsize and smaller brands) provides “a single source of truth” for guest data and creates 360-degree guest profiles, augments these with preferences, social media ambassadorship, customer engagement data, etc., which enables ALL hotel departments to do their job more efficiently and effectively. The more you know about your guests, their preferences, their likes and dislikes, their past stay history, and their RFM value (Recency, Frequency, and Monetary), the better you can deliver value, recognition, and personalized service. AI can make this process a thousand times more efficient and effective. Ex. Operations can now anticipate guest requests and preferences, and personalize customer experiences; Marketing can finally embark on one-to-one marketing and can significantly increase customer engagements via similar audiences marketing. First-party and zero-party guest data have become more precious than gold today due to government privacy regulations as well as browsers and search engines own privacy protections. The moral of the story? Before jumping into futuristic AI connectivity projects with Model Context Protocol (MCP) or Agent-to-Agent (A2A), take care of the fundamentals to prepare for the upcoming Agentic AI upheaval that will, inevitably, take over hotel bookings, guest relationships and personalization over the next years.

Why did Business Travel News write a feature profile on Clarasight this week? Not because everyone in corporate travel is talking about AI agents right now. It's because very few are talking about the data layer underneath them. I sat down with Michael Baker and we got into why that gap matters. Philip Charm and I keep hearing the same thing from travel leaders - that the data exists but it's scattered across TMCs, expense platforms, HR, cards, meetings tools, etc. None of those systems were designed to connect. ⚡ You have to build an AI-ready, reconciled data model first. Only then can you layer in forecasting, automation and agents. That's why Clarasight is growing so fast. We started by building a foundation for modeling emissions originally but to do that we had to solve the fragmentation problem first, which immediately led to travel & finance leaders asking us to solve the same challenges for #spend, #budgeting, #compliance, #approvals, #leakage, #meetings and more. Once we did, one of our largest customers hit within 5% of their originally forecasted travel demand a full year into the program. No more end-of-year travel bans. No more scrambling because someone discovered the budget was already gone. We're now expanding our AI products across data management, analytics and policy compliance, meetings and events planning, and workflow automation. ⚡ Our goal is to become the definitive AI Platform for Modern Travel Teams. Last year our revenue grew ~10x last year and this year we're tripled our team. We got the data right first. The growth followed. But it's all been led by listening and learning from the gaps that not enough people are talking about openly.. and then leveraging AI, software and our team of subject-matter experts to helps enterprise leaders thrive. Do you agree that the real foundation for trustworthy AI applications in travel is getting the data right first? What else aren't people talking about enough? ⚡ (article link in comments) #corproratetravel #clarasight #btn #data #AI #agents #tech

Oh the irony.....AI might be the best way to bring humanity back to hospitality. I know, that sounds backwards. But think about it. Most hotels are drowning in data they can’t use. Fifteen different systems, each hoarding a piece of the guest story. So when a loyal guest walks in for the fifth time, they’re still asked: “Is this your first stay with us?” That’s not hospitality. That’s a missed opportunity. That's a disappointed guest. Here’s the twist: AI can fix this. Not by replacing people, but by giving them what they’ve been missing: context. Imagine a simple dashboard that tells the front desk: ✔️This guest prefers a cold room and two extra pillows. ✔️ They celebrated an anniversary here last year. ✔️ They had an issue with the Wi-Fi on their last stay. Now your staff isn’t starting from zero. They’re starting from recognition. From connection. From humanity. The catch? AI can only help if your data is in order. If your data is accessible. So here’s a bit of advice: if your systems are fragmented or hard to use, getting them unified and data is actionable is step one. At Hapi, we exist to help with exactly that... making it easier for your team to turn insights into genuinely personal guest experiences. Giving your team the ability to make a human connection. The winners in this industry will be the brands that stop treating AI as a gadget and start using it as a tool for their teams to be more… well, human. https://lnkd.in/dyRdnxMy

If we're serious about AI agents and agentic workflows in the tour and experiences industry, we need to start with the boring and tedious bit first: data organisation. Not sure where to start? This is something you can do right now. AI agents will work off what they can access. And in most tour businesses, data lives in booking platforms, inboxes, WhatsApp threads, Google Sheets, PDFs sent to guides, and notes only one person understands! That makes real automation almost impossible. If you want AI to answer guest questions accurately, recommend the right tour, handle availability and pricing, support guides and ops, and personalize pre and post-tour comms, then your data needs to be structured, consistent, centralized, and accessible. Structured means tours, schedules, inclusions, pricing, and policies are clearly defined. Consistent means same names, same formats, same logic across everything. Centralized means one source of truth. Accessible means not locked inside people's heads. Right now, many operators are trying to bolt AI onto messy systems and hoping for magic. The reality is AI doesn't replace operations. AI exposes how good or bad your operations already are. Over the next few years, the operators who pull ahead will be the ones using who cleaned up their data first. I’ll be diving deeper into data organisation for tour and experience brands, exploring how tools like Airtable, MongoDB, Notion and Google Sheets can be used at different stages of scale. I’ll be sharing what works (and what doesn’t) in my Experience Marketing Newsletter. Curious to hear how others in tours and experiences are approaching this. Are you organising your data for AI yet, or still experimenting with tools?

A resort approached me 6 months ago wondering why their dashboard looks healthy but direct bookings have slowly dropped. We started with a simple visibility audit. What we found felt anything but simple. Their website traffic was steady. Their reviews were strong. Their marketing spend hadn’t changed. But their presence, where discovery actually begins, was fading.   The reality is that how guests discover resorts has changed Today, the first interaction rarely happens on your website. It happens inside an AI search, a chat window, or a voice request. ChatGPT now handles over 2.5 billion prompts every day (before the launch of Atlas… this number is higher now)  And this is just one of the many agentic search engines now being used. And not to mention that nearly 60% of Google searches end without a single click.  The answer appears right inside the interface through AI results. A resort’s discoverability isn’t determined just by its website anymore,  it’s determined by how clearly and consistently its information exists across the entire digital ecosystem that AI systems read, learn from, and recommend from. When a guest asks ChatGPT, Google Gemini, or Perplexity: “Find me a resort near Sedona with a spa and hiking trails,” the AI doesn’t open your website. It searches its indexed data sources, your Google Business Profile, OTA listings, structured schema markup, review sites, social data, and third-party travel aggregators. If those data sources are inconsistent,  different addresses, outdated rates, missing amenities, your property is automatically filtered out or misrepresented. When we performed the Audit: The resort’s website was beautiful but……  We found six versions of the property name across OTAs and review sites. 12 different phone numbers online and on the website. Outdated policies listed on Google. Inconsistent amenities listed online. And not a single clean, structured dataset describing the property in a way machines could understand. Their social profiles told one story. Their listings told another. Their schema told none. No schema.org markup. No unified property IDs. No live connection between their PMS, CRM, and booking systems. From a human perspective, it was a five-star resort. From a machine’s perspective, it didn’t exist. In the end we were able to help this resort organize their live data, and improve their visibility. This resort noticed a huge positive shift in their direct bookings, golf bookings, and group bookings after this. And I’m glad to still be working with them today. If you want my company to do a visibility audit on your resort, or want to know how to get started: DM me

So OTA apps are moving inside "Chat". But hotel brands shouldn't simply follow suit and "duplicate" their apps inside ChatGPT. They should ship an agent surface, not a clone. Where this is going: ➜ Apps will live inside personal intelligence. Travel agents (the AI kind) will carry your context—budget, loyalty, trip purpose, companions—across apps and pre-filter results before you ask. ➜ Shared context across apps. Calendar, flights, maps, and corporate policy inform the same session. The user’s intent flows; the app is just the surface. Beyond text. Voice, map overlays, and interactive components become the primary controls; text is auxiliary. ➜ Shareable “intelligence objects.” Guests (or their corporate agents) can share dietary needs, accessibility preferences, and policy constraints once; every downstream app honors them. What hotels should do now: ➜ Structure your inventory and claims. Amenities, walk times, room attributes, sustainability badges, F&B hours—all as verifiable, machine-readable data. ➜ Expose instant booking and pricing APIs. Support real-time availability, hold/commit flows, and clear cancellation policies. ➜ Publish preference and policy hooks. Accept guest/corporate profiles with consented attributes; return explanations aligned to those inputs. ➜ Instrument for “time-to-shortlist.” Optimize for how fast a qualified guest reaches 3 viable options, not raw search volume. ➜ Invest in agent UX. Build a lightweight agent that sits in this shared-intelligence layer: clarify trade-offs, justify recommendations, and complete the booking. Think broader than ChatGPT as another channel. Build for the agent layer first--then package that capability as your Chat app.

The AI Stack Is Forming and Amadeus Already Owns the Core Functions Amadeus is designing the architecture for travel in an AI-first market. Luis Maroto is aligning the business around AI services driving real-time pricing, servicing, search, and payments. Revenue hit €4.6 billion in the first nine months of 2024. This followed sustained investment in core infrastructure and ecosystem depth. Partnerships with Microsoft and Accenture support scale across automation and integration. Amadeus is embedding into airline and hospitality workflows. The acquisition of Vision-Box strengthens biometrics. Voxel adds payments and transaction reach. These moves extend Amadeus across the full guest journey. AI supports over 100 Amadeus functions, including booking optimization, customer service, and search. These tools compound performance. Hoteliers are boosting tech budgets by 16 percent. 85 percent expect AI-driven personalization to lift revenue by 5 percent or more. Amadeus is positioned to capture that growth. Q1 2026 earnings will confirm whether execution matches the strategy. APPLICATION FOR HOTEL COMMERCIAL TEAMS AI has shifted from theory to infrastructure. Execution depends on systems that learn, adapt, and run continuously. Guest decisions are happening upstream. AI filters choices before a guest sees your site. Speed, relevance, and always-on service define performance. Delayed reactions miss revenue. Manual workflows slow down response. AI-driven systems compress time and expand precision. Every function in sales, marketing, and revenue now feeds the data layer. Teams require systems that learn faster than the market changes. FIVE ACTION STEPS FOR HOTELIERS 1️⃣ Centralize Guest Data Capture and structure behavior signals. Train tools with your data. Guide offers with real usage patterns. 2️⃣ Build Commercial AI Workflows Use AI voice, content, and targeting tools that connect across platforms. 3️⃣ Shift Spend to Infrastructure Invest in tooling that replaces manual work with automation and scale. 4️⃣ Launch Always-On Systems Deploy AI voice agents, image generation, and campaign automations. 5️⃣ Restructure for AI Ops Train teams. Assign ownership of systems. Build a test-and-iterate loop. ➡️ Teams with structured AI systems will outperform. ➡️ Speed and precision are now baseline. Need help driving direct revenue, boosting team output, or operationalizing AI? Reach out.