Do you operate a hotel chain and want to calculate budgets automatically? Does your hotel need to predict next week’s purchase orders or how many reservations are going to be cancelled? Do you want to enable check-ins through facial recognition? All this is possible with machine learning.
Machine Learning is a technology that allows computers to learn without being explicitly programmed to do so. Or put another way, they are algorithms that reach conclusions from a set of data, and have the ability to transform data into knowledge.
Types of Machine Learning
Machine learning algorithms can learn in 4 different ways: supervised learning, unsupervised learning, semi-supervised learning or reinforcement learning.
This is the one in which we give the system the solution based on a series of parameters. That is, we provide the system with many examples including the characteristics of each example and its result. In this way, the algorithm “learns” to classify the samples and Machine Learning is in charge of finding the pattern and the internal structure of the information.
Unlike supervised learning, the system is not given the solution. Therefore, the system sees patterns and draws conclusions. In this type of learning we would highlight clustering, which consists of looking for groups that have similarities for some reason. In the hotel sector, it would help us to identify customer segmentations and thus be able to get to know our guests better and offer a more personalized service.
This type of machine learning would be a combination of the two previous ones, i.e., there is an unsupervised stage and a supervised stage. It has been found that unlabeled data (unsupervised learning) when used with a small amount of labeled data (supervised learning), can exponentially improve learning accuracy.
Can machines learn on their own? The answer is yes, and it is through reinforcement learning. Reinforcement learning attempts to ensure that an artificial intelligence learns to decide through its own experience. That is, it is capable of knowing for itself the best action to perform at that moment through an interactive process of trial and error.
A clear example would be the chatbots on hotel websites. The chatbot is a program with which it is possible to have a conversation, both to ask for information and to perform an action. In addition, the latest trend is that reservations can be made through chatbots.
What is the difference between Artificial Intelligence and Machine Learning?
It is important not to confuse Artificial Intelligence with Machine Learning. AI is the general science of creating automated intelligent systems, such as robots or industrial processes. While ML creates algorithms so that machines can perform intelligent projects from the data provided.
How does machine learning fit into the future of the hotel industry?
Machine Learning is gaining momentum in the hotel industry and could help improve many areas of the hotel industry. For example, budgets could be made much more accurate by collecting and analyzing data from previous years. You could also automatically calculate next week’s purchase orders based on occupancy, customer type, nationality, etc.
What would it be like to check in with facial recognition, or to have the room key directly on the mobile device? All this would be possible thanks to Machine Learning. It is important to note that there are repetitive jobs, such as some back office tasks or the check-in procedure, and others that require a more personalized customer service, such as complaint management.
Another great example would be Revenue Management. With a Revenue Management system based on Machine Learning, processes can be systematized and save time. In addition, decisions can be made in a more informed and strategic way.
In short, Machine Learning could be used both to improve the company’s profits and to offer a different and innovative service to the customer. The aim is to unload routine and repetitive work, in order to be able to focus on other types of tasks in which the human factor is essential.
Therefore, to what extent can Machine Learning be implemented, and how do you think Machine Learning will affect the hotel sector in 10 years?