rms

Revenue strategy changes as portfolios grow. What works at the individual property level doesn’t reliably extend across multiple hotels, markets, and teams

AI can make revenue management work leaner and more precise, but without the right prompt, results are mediocre at best or, at worse, harmful

The problem is not that ChatGPT is “bad at revenue management.” The problem is that it does not actually do revenue management at all

This intricate balance between ADR and Occupancy is where an RMS can ultimately help you to maximize your revenue

Not only can pricing become more personalised, but also the entire package and experience. I expect attributes and individualisation to play a bigger role

While the adoption of artificial intelligence in the RMS is rising rapidly, confidence in the technology’s decisions often remains low

A good RMS doesn’t just automate pricing; it also streamlines performance tracking helping small hotel groups compete with big brands and independents

Here is the round up of Hotel Success Stories from our Expert Partners during May, touching on revenue, bookings and guest experience

Of course, not every scenario will be the same. However, without real-time price optimization, you could be leaving revenue on the table

Until leadership not only understands the revenue problem but agrees it’s the hotel’s problem, no tool, strategy, or pricing model will move the needle