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Bookings Are Moving Into the Chat, But Your Guest Data Isn't Coming With It

Why travel and hospitality marketers need an agentic operating layer that acts on the signals they still own

Khan Smith
Khan Smith
Oct 20, 2026
Bookings Are Moving Into the Chat, But Your Guest Data Isn't Coming With It

On August 27, Google started rolling out hotel booking inside AI Mode. A U.S. traveler can now find a room, compare options, review the cancellation terms, and pay with Google Pay without leaving the chat. Marriott, Hilton, IHG, Choice, and Wyndham signed on as launch partners, right alongside Booking.com and Expedia. Two weeks later, Meta launched Muse, a personal AI agent that can plan, book, and pay for travel on a user's behalf, with accommodations expected to follow.

The detail that should get every hotel CMO's attention is a few paragraphs into Skift's coverage. Google passes its partners only the minimum data needed to complete the booking: name, payment, occupancy, and property. The conversation, the comparisons, and the moment the traveler actually made up their mind all stay with Google.

For those following along, that means the booking is moving into the chat, and most of the signal about why it happened remains there. For an industry where Online Travel Agencies (OTA) already generate close to twice the bookings of hotel-owned digital channels, that's one more layer between the brand and the guest. AI-referred traffic to U.S. travel sites grew 194 percent year over year in May, according to Adobe, and 56 percent of U.S. travelers used AI on at least one trip in the past year, according to Phocuswright.

Travel's Timing Problem Just Got More Expensive

We've been talking with a lot of travel and hospitality marketing teams this year, and the pattern is consistent. The problem isn't a shortage of tools. Most hotel groups already run a PMS, a CRS, a revenue management system, a booking engine, a loyalty platform, a CRM, an ESP, a rate shopper, and a handful of paid media accounts. Each one works fine on its own. Nothing connects them, so the marketer ends up being the connective tissue. According to The State of Distribution 2026, more than 80 percent of hotel commercial teams still spend one to two days a week building and analyzing reports by hand.

That manual overhead shows up as lag. A competitor drops rates overnight, revenue management sees it at 6am, and marketing hears about it Thursday, sometimes after a campaign promoting the old price has already gone out. A guest checks out on Sunday and the post-stay email fires on a timer somebody set months ago. A top-tier member who stayed with you all year gets the same offer as someone who subscribed yesterday.

In most industries a late decision is frustrating. In travel it's expensive, because an unsold room night can never be sold again. It's also getting harder to absorb. U.S. hotel loyalty program fees grew 3.9 percent in 2024, faster than rooms revenue at 2.7 percent, according to CBRE. And as AI agents take over more of the top of the funnel, the first-party data a brand still owns (loyalty activity, stay history, booking behavior) becomes the most valuable asset it has. Acting on it days late wastes that advantage.

Where Agentic Marketing Changes the Equation

At Kana, we define agentic marketing as an operating layer built to learn, so a marketer's judgment and decisions compound instead of getting rebuilt from scratch every time. In travel, the practical meaning is simple. The system watches the signals you own, connects them across the stack you already run, and puts a recommended action in front of your team while it still matters.

The appetite is already there. Half of hotels say they're adopting AI now, and 82 percent plan to ramp up usage in the next 12 months. The results just haven't caught up. More than half of hotels use or are procuring generative AI, yet fewer than one in ten say it has cut their manual work by more than 30 percent, and 69 percent still have staff entering guest preference data by hand.

That gap comes down to architecture and governance. Duplicated guest profiles and data spread across five or six systems don't disappear when AI gets layered on top. They get amplified. So the better question for a travel CMO to ask any vendor is what it's actually prepared to own: the integrations, the governance, the audit trail, and the maintenance when models and platforms change.

How We Recommend Travel and Hospitality Teams Begin Agentic AI Adoption

Sequencing matters more than speed. We recommend travel and hospitality marketing teams progress from on-demand agents that answer a defined question, to continuous agents that monitor in the background and flag what changed, and finally expand into autonomous agents only as governance and confidence build. Teams that skip ahead tend to discover their guest-profile problems at the worst possible moment, which is usually the run-up to peak season.

In practice, most teams can see value within 30 days by connecting their top three to five data sources. Here's where we'd start:

  1. Put the rate move in front of marketing the same day. Your rate shopper watches competitive pricing for revenue management. Marketing needs the same signal, with the evidence attached, so messaging and offers can respond before a campaign promoting yesterday's price goes out.
  2. Stop sending first-timer offers to your best members. Use recent member activity (browsing, app opens, stays, tier status) to recommend each guest's next offer for the team to approve. When loyalty costs are growing faster than rooms revenue, every offer should be traceable to incremental revenue.
  3. Build the list worth re-engaging. Replace static win-back exports with segments built directly from CRM, loyalty, and booking data, suppressed for who is actually eligible today. Nearly 22 percent of OTA bookings at independent hotels get cancelled, so a list pulled last week is already wrong.
  4. Time outreach to the booking window, not the calendar. Once segments and offers are reliable, trigger post-stay and win-back outreach when a guest is ready to book again, instead of when the automation was configured to fire.
  5. Catch spend drift before the monthly readout. Watch live spend across channels and flag anything drifting from the brief, with a proposed reallocation ready for approval.

One more thing worth doing now: treat AI-referred traffic as its own channel in your measurement. AI search already accounts for roughly 4 percent of hotel reservations, yet 55 percent of hotels report little or no change to their distribution strategy. When Google and Meta only hand you the booking, the signals you capture on your own properties and in your own loyalty program carry even more weight.

Why Kana Is Built for This

Travel brands are usually offered two choices for new software. Build it, which is expensive and never quite finishes. Or buy it, which fits generically and then takes months of integration work. Kana takes a third approach we call Build-With: applications shaped to a travel brand's actual workflow, configured to its data, and governed by its policies, delivered at the speed and cost of buying.

That means no rip-and-replace and no data migration. Kana connects by API and sits on top of the systems a hotel group or travel brand already runs, including Opera, Duetto, IDeaS, and Salesforce. Our Forward Deployed Engineers work inside your environment during onboarding, and the knowledge graph underneath your applications gets smarter with every interaction. When models update, platforms change, or regulations shift, the maintenance stays with Kana. It doesn't land on a marketing team that was never staffed to carry it.

Kana's Personalization, Category Intelligence, Audience Builder, and Campaign Orchestrator applications are built to run the guest lifecycle as one connected loop, from the first rate signal to the post-stay offer.

The AI discovery  and agentic commerce layers are going to keep changing, and quickly. The travel and hospitality brands that come out ahead will be the ones acting on what they know about their guests at the speed of their own pricing. For a deeper look, download our white paper, Moving at the Speed of Your Pricing. And if you'd like to see what this looks like on your own data, get in touch today.

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Khan Smith
Khan Smith
Oct 20, 2026
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