Here are few of the stories that caught our attention over the week with some of our takeaways. Watch the video for a summary or scroll down for the analysis.
Story 1
Rate Leakage: The 98% Problem We’re Still Not Measuring Properly
Web in Travel’s conversation with Steve Quan, SVP of Hotel Enterprise Partnerships at Expedia Group, reveals that 98% of hoteliers are affected by rate leakage, yet most are dramatically underestimating its cost.
The Visibility Problem Quan’s central argument challenges the industry’s tendency to blame “bad actors” for rate misuse. The real culprits? Fragmentation and complexity baked into how we operate. The issue isn’t just that rates leak—it’s that hoteliers don’t know what they don’t know. Without comprehensive visibility into where and how rates are being misused, we’re operating on incomplete information, making it impossible to quantify the true revenue impact.
The management principle is straightforward: if you can’t measure the problem, you can’t manage it. And right now, most hotels are flying blind.
Centralisation vs. Control The proposed solution requires hotels to abandon their reliance on siloed spreadsheets and manual processes. Quan advocates for three pillars: automation to reduce errors, centralisation to create unified visibility, and organisational alignment to ensure everyone’s working towards the same goal.
The resistance to centralisation stems from a fear of losing control. But Quan argues the opposite is true—centralisation enables more powerful, network-wide enforcement. Expedia’s network effect model can police and penalise bad actors more effectively than any individual hotel managing spreadsheets across dozens of markets.
He draws a telling comparison: we’re comfortable centralising our personal finances on dashboard apps, yet the hotel industry clings to fragmented, outdated methods for managing distribution worth billions.
AI as the Game Changer for 2026 The most significant shift coming isn’t just better monitoring—it’s predictive intervention. AI’s role in 2026 will be moving the industry from reactive firefighting to proactive prevention. Instead of discovering rate leakage after it’s happened and scrambling to fix it, AI systems will predict where leaks are likely to occur and intervene before rates hit unauthorised channels.
Quan’s ultimate vision is making “rate misuse” an obsolete term entirely. Whether that’s realistic remains to be seen, but the direction is clear: better data, better systems, better enforcement.
Story 2
Airbnb’s Hotel Play: Threat, Opportunity, or Just Another OTA?
Hospitality Net’s analysis on Airbnb’s evolution into a full-service OTA reveals a defensive move driven by Booking.com now generating over 85% of Airbnb’s short-term rental volume.
The Defensive Pivot Airbnb’s adoption of a 15.5% host commission structure and elimination of guest service fees directly mirrors established OTA models. Max Starkov notes that the novelty of Airbnb has “worn off” and short-term rentals have become “mainstream, commoditised product.” The company needs hotels to reinvigorate its product line and bottom line, positioning itself as an “everything app” for travel—though notably lacking the loyalty programmes that Booking.com and Expedia have built with over 200 million members combined.
The Three Perspectives Industry experts are sharply divided. The first camp sees this as redundant—Muhammad Tanveer argues it’s “less innovation and more defence,” just another reseller in an already crowded ecosystem. Simone Puorto suggests the market has reached saturation, with intermediary models that are “practically indistinguishable.”
The second perspective views Airbnb as a welcome disruptor to the Booking.com/Expedia duopoly. Harald Bindeus argues a strong third competitor creates opportunities, whilst Pablo Torres sees it as a tool to rebalance properties relying on Booking.com for 60-80% of their online volume. When OTAs compete, hotels can benefit—if they maintain controlled distribution.
The third, more nuanced view suggests the question itself is wrong. Alessandro Crotti points out hoteliers don’t control whether new OTAs emerge. Chinmai Sharma argues Airbnb’s move “exposes an existing one”—the dominance of OTAs stems from their frictionless, trusted, personalised shopping environment. The solution isn’t resisting intermediaries but making the direct channel equally competitive.
The Audience Opportunity What makes Airbnb potentially valuable isn’t another distribution channel—it’s access to a distinct demographic. James Bishop notes these are platform-loyal users who start their search on Airbnb without comparing elsewhere. “These aren’t guests hotels are losing to a competitor—they’re guests hotels couldn’t guarantee being able to reach otherwise.”
The audience skews younger, more experience-driven, and more international. Mark Fancourt points out they carry that “experience-first” mindset into hotel bookings. Niki Van den Broeck emphasises this works for properties with “local, unique character”—anything resembling big chain standardisation won’t succeed.
The Conditions for Success For hoteliers considering Airbnb, four conditions are non-negotiable: ensure your product fits the platform’s aesthetic expectations, maintain controlled distribution with dynamic inventory, implement rigorous tracking of net RevPAR and acquisition costs, and prioritise your direct channel. As Pablo Torres puts it, “Airbnb should be one more spoke in the wheel, not a new single point of failure.”
The broader pattern Vassilis Syropoulos identifies is worth noting: new players enter, commission wars benefit hotels initially, customer acquisition costs explode, costs transfer back to hotels through higher commissions, consolidation follows. We’ve seen this cycle before.
Story 3
How AI Agents Could Reshape Hotel Distribution (and Why Your CRS Matters More Than You Think)
Platform Aeronaut’s analysis on agentic AI presents a compelling case that Central Reservation Systems are positioned to become the new gatekeepers in hotel distribution.
From Browsing to Transacting The current distribution model—OTAs, GDS, metasearch—was built for human web browsing. AI agents operate fundamentally differently: they don’t browse websites, they transact. They require direct, programmatic access to the richest, most accurate, most up-to-date data to execute tasks autonomously.
This shifts power from “top of the funnel” aggregators to systems “below the funnel”—the operational systems that hold the canonical source of truth. OTAs are structurally misaligned because they don’t own the rates, availability, and inventory data. They use cached availability and have opaque pricing logic. The CRS, by contrast, is the definitive source for ARI, the pricing logic, and the transactional rail.
The Emerging Model Context Protocol As AI agents become the primary means of booking travel, the Model Context Protocol (MCP) standard will provide them with direct programmatic access to hotel data. The industry is moving from optimising for Search Engine Optimisation to optimising for MCP.
CRS vendors are investing heavily in this future. SynXis has launched Concierge.AI, an AI “Booking Agent” that recommends rooms, answers questions in over 50 languages, and completes bookings via APIs. Amadeus is building the “pipes” for MCP agents to access live rates and availability. Cendyn is explicitly investing in APIs and MCPs to feed “AI helpers,” notably the only vendor name-checking MCP directly.
What This Means for Other Systems Booking Engines will evolve from UI layers to API layers, surfacing conversational experiences whilst the CRS executes the transaction. Property Management Systems will become the hub for AI-driven in-stay servicing—the right place for agents to manage modifications, extensions, and mid-stay requests.
The analysis concludes with a stark prediction: “If OTAs were the UI layer of the last generation, CRS will be the API layer of the next.”
The Unresolved Questions The thesis raises important concerns. Will CRS vendors become the new gatekeepers, or simply middleware beneath the true gatekeepers—the AI operating systems like Siri, ChatGPT, or Gemini that own user intent? Could CRS vendors become the next monopolistic rent-seekers, replicating the dynamic hotels currently face with OTAs?
And if AI agents optimise purely on price, cancellation terms, and availability, could this accelerate hotel commoditisation and margin compression? The entire premise rests on MCP adoption—questions remain about whether it’s a genuine paradigm shift or hype.
Story 4
Black Friday 2025: The Direct Channel Data You Need to See
The Hotels Network’s analysis of 1,982 client hotels reveals that properties running dedicated Black Friday campaigns achieved 60.5% revenue growth versus just 4.4% for non-participants.
The Performance Gap Hotels with active campaigns didn’t just see marginal improvements—they experienced step-change performance across every metric. Direct bookings increased 30.8% compared to 2.8% for non-participants. Booking engine conversion rates surged 56.6% whilst non-campaign hotels saw theirs decline by 0.6%. Unique website visitors grew 4.6% versus a 4.4% decrease without campaigns.
Perhaps most telling: Average Revenue Per User jumped 56.3% for campaign hotels whilst dropping 8.0% for those sitting on the sidelines.
Discounts Don’t Erode Value The concern that Black Friday promotions damage profitability is demonstrably wrong. Well-designed campaigns increased both booking volume and booking value. The 56.3% surge in ARPU for participating hotels shows that travellers actively searching for offers during this period are prepared to book longer stays or premium options when presented with compelling reasons to do so.
The data comparison period (18th November to 2nd December versus 18th October to 2nd November) eliminates seasonal variations, making the campaign impact clear. Booking engine searches increased 16.2% for campaign hotels versus 3.6% without—targeted offers successfully moved users from browsing to active consideration.
The Broader Implication Black Friday has evolved from a promotional tactic into a high-intent demand moment. Travellers expect offers, they’re actively searching, and they’re prepared to book. Hotels meeting this demand with targeted campaigns capture significant growth. Those without promotions risk being overlooked entirely in a competitive period.
The success provides a repeatable model for other high-intent moments throughout the year—Valentine’s Day, Mother’s Day, shoulder season pushes. The methodology applies: identify the moment, create the campaign, track the performance rigorously.
Story 5
From Rooms to Relationships: Why RevPAR is the Wrong Metric
The Mews and Skift research report argues that the traditional hotel business model—selling rooms and measuring success through RevPAR—fundamentally limits growth potential and investor confidence.
The Limitations of “Heads in Beds” The room-centric model treats customers as commodities, values them only during overnight stays, and ignores revenue opportunities from non-room assets and local community engagement. Average Daily Rate and Revenue Per Available Room are calculated based solely on room purchases, creating a blind spot for all other customer interactions and spending.
Skift CEO Rafat Ali’s assessment is damning: the industry has “created a travel experience that feels hostile to the very people we’re supposedly trying to attract.” Mews Founder Richard Valtr argues hotels should measure relationships in hours rather than nights—you have a relationship with that customer over 24 hours, 72 hours, or in the case of loyalty members, 365 days or even a lifetime.
The financial performance forecasts reinforce the urgency for change. U.S. hotel occupancy is projected to decline from 63% in 2024 to 62.5% in 2025. RevPAR is expected to decrease by 0.1%. Global hotel investment rates have reached their lowest point in over a decade, with private-equity-sponsored deals in the United States plummeting 85% year-to-date.
The Community Asset Model Forward-thinking brands are repositioning their properties as “third places”—welcoming spaces between home and work serving both travellers and locals. The guiding question shifts from “What can I sell?” to “What can people use?”
Staypineapple’s Boston hotel features the Trophy Room, a community bar occupying 85% of ground floor public space. President Dina Belon notes, “Many people who come to Trophy Room may not even know there’s a hotel in the building.”
The commercial proof is in Ennismore’s numbers. Founder Sharan Pasricha states that over 60% of revenues come from sources other than room sales—restaurants, bars, coworking spaces. “Owners and investors love that diversification of revenue.”
The Mews Spaces Data Nearly one-third of Mews customers use Mews Spaces to offer additional bookable services like parking, meeting rooms, or gym memberships. Reservations for these non-room services grew over 300% year-over-year between January-April 2024 and the same period in 2025 (from 145,665 to 482,697). Since launching in 2021, 1.5 million such reservations have been made.
Revenue Per Available Guest The proposed metric shift to RevPAG positions the guest profile as the central value driver, enabling operators to track all interactions and purchases across every touchpoint. The challenge is implementation: lack of standardisation on defining a “guest,” complexity compared to RevPAR’s simplicity, concerns about brands gaming the metric, and the technology requirements for integrated data systems.
Staypineapple’s Dina Belon highlights the RevPAR problem clearly: “ADR and RevPAR provide an excellent snapshot of room revenue but tell us nothing about profitability. A high RevPAR can be misleading if it’s achieved with deep discounting that erodes margins.”
The technology enabler is integration—Property Management, CRM, and Point of Sale systems connected to create a single source of truth for each customer profile. Paradise Resort Gold Coast used Mews to implement bookable experiences with unified guest profiles, increasing RevPAG by making upsells simple at multiple touchpoints whilst massively reducing manual work.