Weekly Insights. May 9, 2026

Different types of hotel room: Classifications explained

The article starts as a guide to standard hotel room classifications like single, double, twin, deluxe, and suite types, but it really expands into how room categories affect pricing, positioning, and revenue strategy, then moves into newer room concepts such as wellness rooms, pet friendly rooms, smart rooms, and highly experiential room designs, before finishing with attribute based selling and the idea that hotels can move beyond fixed room types by selling individual features and benefits more strategically.

Your AI Agent will make you the smartest person in an empty room

The article is about the limits of AI agents in hotel revenue work, arguing that saving a revenue manager time is not the same as improving hotel performance, then showing how forecasts often stay trapped inside one department while sales, marketing, F&B, and operations keep making decisions without that insight, so the real value comes from turning the forecast into a shared operating tool across the whole hotel first and only then layering AI on top.

Hotel site selection: A market-first approach to hotel location analysis

The article explains how hotel site selection should start with market and submarket analysis before land, brand, or design decisions, then walks through the main signals developers and investors should study such as demand and supply balance, long term performance, volatility, and submarket differences, before showing how historical data and forward looking forecasts can be used together to test feasibility, shape underwriting assumptions, and reduce downside risk early in the development process.

Transforming hotels with business intelligence for hotels

The article is a general overview of how business intelligence can be used in hotels, covering the main benefits across revenue management, guest experience, operations, marketing, and competitor tracking, then moving into the role of AI within BI tools, what features hotels should look for in those systems, and a simple step by step guide for implementation.

The real reason your direct bookings are not growing

The article is a practical breakdown of why direct bookings stay flat even when hotels think they are prioritizing them, focusing less on OTAs themselves and more on the hotel’s own weak points, such as a clunky booking engine, poor mobile conversion, hidden or ineffective best rate guarantees, lack of meaningful direct booking perks, weak metasearch presence, unnoticed parity violations, and missed pre arrival and post stay communication.

What does it actually take to get your hotel on ChatGPT?

The article explains what hotels actually need to do to show up inside ChatGPT, arguing that it is less about building custom tech and more about making hotel content structured, accurate, and AI readable, then walking through Lighthouse’s process step by step, from automatically gathering hotel data into an AI data hub, to placing the property inside The Hotels Network app in ChatGPT, to formatting content for AI discovery through GEO, and finally addressing practical concerns like website redesigns, booking engine limitations, and ongoing maintenance.

Uber just entered your hotel. The question is not whether that is a threat. The question is what signal you are about to lose

The article is less about Uber adding hotel booking and more about what hotels lose when another platform sits between them and the guest, arguing that Uber’s real advantage is not the reservation itself but the behavioral data around search, price sensitivity, location, movement, and in trip habits, then broadening that point to show how Google, Apple, and AI platforms are also capturing more of the traveler relationship, before ending with a call for hotels to build stronger internal systems for collecting, connecting, and using their own guest intelligence instead of focusing only on commissions and distribution.

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