In the latest Thematic World Panel, we posed the question of how primary data extractions from the property management system (PMS) can be used for machine learning (ML) to the grow a hotel or heighten productivity. With a range of astute viewpoints from respondents, there are two main themes that the answers revealed.
Using interfaces to access the multitudes of information housed within a hotel s property management system (PMS), technology vendors have on their hands a literal treasure trove of first-party training data for machine learning applications. Any primary data extraction must nevertheless be focused around specific use cases that must be tested and verified before deploying in a live environment. Thus far, we ve seen lots of discussion around what s possible in the abstract for machine learning, but outside of perhaps chatbots and algorithmic rate optimization recommendations, many of the purported use cases are not practical for the here and now.
In the early stages of Revenue Management, cranking up rates when the hotel was on a clear path to selling out was about all it took to be a successful Revenue Manager. But as digital transformation has taken hold in hotels, the role, and the definition of success, have evolved greatly. Once the gold standard, technical knowledge and decent Excel skills are now table stakes. Today s successful Revenue Manager must focus far beyond forecasting and setting prices. A mastery of the constantly evolving distribution technology landscape, including a keen understanding of every step of the digital customer journey is essential to optimizing market share and total hotel profitability.Today s customer experience begins way before the guest steps foot on property. The ease of finding information before booking, transparency and fairness in pricing, and the effective collection and dissemination of every customer s specific needs form the foundation of a successful hotel stay. And the proliferat
To four airlines, CarTrawler chief commercial officer Aileen McCormack said, ancillary revenue is already the predominant revenue source. He calls this phenomenon the ancillary revenue revolution. However, in our industry, up/cross-selling seems to be perceived as mainly a vanity metric.
For as long as most hoteliers can remember, RevPAR has widely been accepted as the most critical hotel performance KPI. Taking both occupancy and average rate into consideration, RevPAR indicates how successful the hotel has been filling its perishable inventory AND the overall caliber of business that it was able to fill it with. Back then, more RevPAR simply meant more profit.