The guide details 11 criteria for selecting 5-10 direct competitors, from location and price to amenities and online presence, with automated tracking solutions.
Comprehensive guide covering real-time pricing strategies, algorithms, and best practices for hotels to maximize revenue through market-responsive rate adjustments.
EHL students analyzed 65 guest interviews and 869 reviews to identify how hotels can incorporate quiet luxury through secluded locations, local materials, and authentic cultural experiences.
MCP enables AI tools like ChatGPT to display live hotel rates and availability, moving beyond generic responses to real-time booking information.
The guide outlines five AI agent types—reflex, model-based, goal-based, utility-based, and learning—with hybrid approaches recommended for balancing autonomy and control in production environments.
Lighthouse provides independent hoteliers with practical SEO tactics including Google Business Profile optimization, review management, and direct booking integration to compete with OTAs.
The guide outlines six steps for hotels to leverage reviews for bookings, from monitoring feedback to automating responses across platforms.
This educational guide explains 15+ AI terms that hoteliers need to understand as travelers increasingly use ChatGPT and similar platforms for trip planning and booking.
Comprehensive guide on converting OTA guests to direct bookers through staff training, automated email sequences, and incentives to reclaim up to 30% commission fees.
WSJ examines the financial missteps and strategic failures that led a major hospitality company from $2B valuation to bankruptcy and property evictions.
Branded residences are luxury homes associated with well-known brands that offer residents hotel-like services and convenience. Rising demand is coming from experience-driven individuals seeking unique and exclusive living.
You have revenue hiding in plain sight…and it’s slipping away.
When most people think of hotel upselling, they often think of it as offering a guest a bigger room at check-in. But today, upselling in hotels means so much more. Every single interaction you have with a guest — from booking to pre-arrival communications to in-person conversations — is an opportunity to create both value for your guest and revenue for your property. THere’s just one key difference, and that lies in how you approach it.
In hospitality, understanding the difference between a hotel and a resort is key in order to provide guests with the right experience. Each type of accommodation takes a different approach and has its own appeal, which means that the way they operate and the services they offer can vary significantly.
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.