What Is MAPE? A hotelier’s guide to forecast accuracy
As a hotelier, you’ll know the frustration: you build a forecast you trust only to see actual results veer wildly off course.
As a hotelier, you’ll know the frustration: you build a forecast you trust only to see actual results veer wildly off course.
A busy hotelier has just wrapped up their best August ever - traditionally it has always been a strong month, but this year it’s been non-stop action. Multiple sell-outs, countless rooms turned, and after closing the books, the overworked team is ready for a much-deserved breather.
Travelers now book through a variety of channels – direct websites, online travel agencies (OTAs), corporate agents and more – making it crucial for hotels to be everywhere their guests are searching.
As a revenue manager, if you focus solely on room income, you risk overlooking valuable contributions from other parts of the property that can significantly boost your bottom line, such as F&B, spa services and paid add-ons.
Two guests book the same property. Same city. Same age. Same check-in date.
The moment AI agents can plug into the systems your hotel already runs on (PMS, POS, RMS, CRM, etc.), they stop being expensive toys with fancy language models and start behaving like digital coworkers. And let’s be clear on the semantics here: not “assistants.” Real (well, kinda) colleagues, capable of executing actual operational work: updating bookings, managing inventory, triggering maintenance, orchestrating systems and processes. This is the fundamental shift we’ll be witnessing over the next few months/years: the move from artificial intelligence as an interface to artificial intelligence as an infrastructure. Until now, most so-called “AI” in hospitality has been confined to shallow use cases, like chatbots, recommendation engines, and flashy BI dashboards. Useful? Sometimes. Transformational? Nah… And the reason is simple: intelligence, whether human or artificial, without access is just performance. You can have the most advanced system in the world, but if it can’t interact with your day-to-day ops (pull a reservation, update a status, execute a workflow), then it’s just another layer of abstraction. Another system to manage, rather than a system that manages for you. This is where the Model Context Protocol (MCP, for short) comes in. MCP is a protocol. A shared language. A neutral standard that can (finally) give AI systems the ability to operate inside your tech stack, and not around it. And when that happens, everything changes.
A guest walks up to the front desk. The receptionist glances at the screen and already knows the guest prefers feather pillows, skipped housekeeping during their last three stays, and charged over $600 in spa and F&B services the last time they were here. Housekeeping’s mobile device pings with an early arrival request. Meanwhile, the marketing team receives a real-time trigger to offer the guest a spa voucher tailored to their usual treatment. All of this happens without a single email, phone call, or Slack message.
True hotel customer loyalty reveals itself in moments like this: A guest walks into your lobby after a long day of travel, and your front desk agent greets him by name, Welcome, Mr. Johnson! It’s so nice to have you back for a third visit with us. Would you like me to send up a late-night snack? Maybe a slice of that chocolate cake you loved last time?
AI isn’t magic. Rather, it’s pattern recognition at scale. And like any pattern recognition system, its output is only as good as its input. Which is why AI’s promise of personalized experiences, automated service flows, real-time recommendations often fall flat in fragmented tech environments. If your PMS, POS, CRM, and housekeeping tools aren’t talking to each other, then your AI is only guessing.
As AI tools like ChatGPT, Perplexity, and Claude become the new search engines, a new kind of optimization is emerging: GEO — Generative Engine Optimization.
Picture a scenario where a hacker poses as an employee and tricks IT support into resetting credentials, bypassing multi-factor authentication and gaining access to core systems. That’s exactly what happened to one of the world’s leading casino brands in 2023, when a social engineering attack brought down everything from check-in kiosks to room keys and slot machines. Operations were disrupted for over a week, costing the company more than $100 million in lost revenue and leading to a $45 million class-action settlement.
Imagine this: A guest walks into your hotel. The front desk greets them by name, already knows they prefer a room away from the elevator, and offers a complimentary drink, the same cocktail they ordered at your rooftop bar during their last stay. At breakfast the waiter suggests asks if the guest wants the usual omelet or the menu to try something new, and at checkout, they’re offered a late checkout because their flight doesn’t leave until 8 p.m.
When we say “AI agents,” we're not talking about the suit-wearing, memory-wiping types from Men in Black, but these new agents might be just as transformative. In the world of hotel tech, AI agents are emerging as intelligent, task-driven assistants that work behind the scenes to simplify operations, boost efficiency, and create better guest experiences. Instead of battling aliens, these agents are here to tackle fragmented systems, reduce manual workloads, and unlock a smarter, more connected future for hospitality. And unlike the old “app-for-everything” approach, agentic AI offers a more agile, scalable way to run your hotel.
With changing consumer demands, new technology, and more competition, travel and hospitality organizations need to adapt their operations, particularly in procurement. Data-driven decision-making has become a critical component of successful procurement strategies.
With the distributed nature of hospitality locations and franchises come various procurement challenges, such as differing requirements, delivery complexities, and communication hurdles.
Sustainability continues to be an important consideration for the travel and hospitality industry, as illustrated by the 83% of travelers who highlight the importance of sustainable travel to them.
There are over 55,900 lodging properties in the United States, according to the American Hotel and Lodging Association. Some of the largest hotel chains own, run, or manage thousands of properties.
Does your loyalty program need a little zhuzhing up? In case you missed the memo, points-based loyalty programs just aren’t as exciting as they once were. Travelers are expecting more from hotel brands, with 79% of Gen Z and Millennial travelers saying they care more about the experience than the cost of the trip.
One of the hospitality industry’s key bottom-line metrics, gross operating profit per available room measures the relationship between hotel revenues and expenses. In general, the better you understand GOPPAR, the better you will be at turning revenue into profit. That is why it is important to benchmark your GOPPAR, along with the other key P&L metrics, on a consistent basis.
The hospitality industry thrives on innovation, and technology sits at the forefront of that progress. From checking in to enjoying their stay, information technology is reshaping the guest experience, allowing hotels to not only keep pace but to truly excel. It is the secret ingredient for a smooth-running operation and an unforgettable guest experience. So, what’s the role of facial biometric authentication technology in the hospitality landscape?