Today, hotels are so ubiquitous that we rarely think deeply about them or their origins. But their history goes all the way back to ancient Greece as an “establishment providing accommodation, meals, and other services for travelers”.
NB: This is an article from GuestCentric
Naturally, hotels started off with very little technological support. However, in the course of their long history, hotels have been impacted by several technological breakthroughs – and in such diverse areas as transportation, energy, communications, and networks. One of these major breakthroughs was the Internet, which brought the web and then Online Travel Agents (OTAs).
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Personalized Prices – The next step in Hotels’ Online Presence?
Many studies have been published about online personalization and how it helps sell more or increase revenue through cross-selling or price tuning techniques. But what does that really mean in practice, for hotels?
Not all hotel guests are the same, and not all consume the same products and experiences on property. If online data points like traffic sources and clicks provide information about the guest’s intent, the data on the hotel CRM is also compelling, because it’s a more robust indicator of what the guest really wants.
By combining data from your CRM with your guests’ online behavior, you can build truly personalized offers for guests. Not only can offers be personalized, but algorithms can also build personalized pricing. With AI, we can have real-time price personalization on hotel booking engines.
Casino hotels provide a good example of how to combine data from different sources to provide personalized pricing according to the guest profile. If John, who is not a player, is booking a room to just enjoy a fun night out at the casino with his friends, he will have a different price from his good friend Martha who is a regular player at the same casino.
But this doesn’t mean that every regular player has the same price as Martha. It doesn’t even mean that Martha will have the same price every time she books at the hotel. The more Martha visits the hotel, the more the algorithm knows about her and will digest this data together with hotel data like occupancy, weather, events, and many others to give Martha the price that best fits her profile at that specific time.
Whether you’re analyzing clicks to see the guests’ intent or diving into your CRM to see what products guests actually like, you can use these metrics to personalize prices for your guests. But remember, the more information you have about your guests, via their journey through your website or the offers they pay for, the better you will be able to personalize the guest prices.
It is important to note that personalized it’s not synonymous with lower price. The objective is to increase the conversion rate of your website and booking engine by providing the guests with a price that is aligned with their expectations.