data
Why AI is Not Enough: 7 Things to Sort Out First
There is immense pressure to acquire AI solutions immediately, often causing leaders to rush into implementation before laying the proper groundwork
How Model Context Protocol (MCP) Connects AI to Hotel Systems
An MCP is not a system of record. It eeceives structured requests, routes them to the correct system, and translates responses into AI-readable formats
The WhatsApp Trap: Why Hotel Operations Slip Through Cracks
The question is not whether WhatsApp is convenient, but whether it’s exposing your operation to missed tasks, inconsistent service and data privacy risk
Your Guests Already Told You Everything. Are You Listening?
Hotels that start unifying their guest database will have a compounding data advantage. They will know guests better and convert more direct bookings
The Hallucination Crisis: Not an AI Problem but a Data Problem
Modern AI is a prediction engine. When the data it receives is incomplete or ambiguous, it fills in the gaps. That is a hallucination
How AI is Pushing Past Hotel Guest Personas
It is unwise for hotels to rely solely on hotel guest personas. The way forward is interaction informed data and understand why guests make decisions
You Hired a Revenue Strategist But You Are Using Them as a Clerk
In most hotels, the revenue manager role has been redefined – not by anyone’s intention, but by the absence of the right infrastructure
Why Revenue Management is Harder for Small Hotels
When revenue management happens intermittently, independent and boutique hotels can miss the window to capture higher rates or improve profitability
How Will Commercial Role Evolve as AI Absorbs Hotel Analytics Work
Forecasting, excel modelling, pattern detection, scenario simulation. These were once the differentiators that defined revenue and commercial leadership
Why Best-of-Breed Beats All-in-One for Revenue Managers
Bringing together best in breed business intelligence and competitive rate intelligence, giving revenue managers something all-in-one platform rarely can
