As Radio Futura sang at the beginning of the 80s, “The future is here“. Artificial Intelligence is being applied to the tourism sector through Deep Learning. But … what is Deep Learning? Broadly speaking, it is a part of AI, and, in turn, a branch of Machine Learning.
It studies how to imitate the logical processes that the human brain performs while learning, so that computers can reproduce them artificially. In this article, we will try to clarify how these sciences impact on the tourism industry.
We will see individually each of these concepts, which are leading a new technological revolution whose potential impact on humanity is still incalculable:
What is Machine Learning?
In short, it refers to machines capable of evolving and improving on their own through “learning”. Thus, machines can emulate the learning processes of the human brain and “learn” to be better. Thanks to this, computers can go beyond their mere role as programmable equipment, giving them the ability to think for themselves. They can recognise patterns, develop skills and knowledge to improve, and do most of the work currently scheduled on their own. These processes eliminate the constant need for human supervision and improve efficiency.
What is Deep Learning?
This method is related to the learning that allows a system to discover by itself the means to organise raw data. Although it belongs to the same family as Machine Learning, it involves specific algorithms. It is a field of futuristic technology with untapped potential, having applications in many disciplines, mainly Artificial Intelligence, Data Analysis and Automation.
Application in the tourism industry
The tourism industry is based on services that include travel, transportation, accommodation and similar services. It is a complex ecosystem in which billions of dollars change hands every day. Like any other multimillion-dollar industry, it depends on technology for its daily operations. In such a huge sector, there is a constant need for fresh and innovative technology to make business processes more efficient and increase profitability.
It is an industry that meets the customers’ wishes, more than their needs. Therefore, competitors strive to offer a better service at a lower price to their customers. Resorting to ML and DL can improve these strategies.
Prediction of seasonal demands for services
Talking about tourism means talking about a business marked by the seasonality of demand. This temporality may or may not be linked to climatic seasons. In any case, it is during those peaks when tourism- product suppliers have the opportunity to earn more money and wish to capitalise on this opportunity.
Deep Learning can be applied to achieve that goal. A computer can easily and accurately find the correlation between the factors that cause this seasonal demand by analysing raw data from the past and predicting the future trend. This process, called Predictive Analytics on Time Series, uses the patterns of the past to predict future events.
Tourism-product suppliers use competitive prices as one of their major strategies to attract customers. Companies try to provide price adjustments without compromising their profits to attract the maximum number of customers. Here, Deep Learning proves to be useful.
Seasonality, the history of the hotel or tourist service, local events, competition or promotions of third parties… all these data can be analysed through predictive models that can be used to offer the best possible prices, providing companies with an advantage on the market.
For a decade, important travel sites such as TripAdvisor and Expedia have used recommendation engines to offer users the holiday packages that best fit their consumer profile. The engines collect budget-specific data, preferences and a customer’s details to give you personalised travel recommendations. Information acquired from various sources and service suppliers is used to find suitable alternatives by comparing options using a Deep Learning program.
The customers of the travel industry are varied, and so is their consumer profile. Their demands and expectations are highly disparate. Meeting them individually is the success measure of any company in this sector. All customers want to be treated according to their preferences, and that is why all the sectors that have such a broad target audience apply market segmentation. In this process, the entire spectrum of customers is subdivided into segments that have similar characteristics and, more or less, the same demands and expectations. Thus, a much more personalised and specialised service can be offered.
When applying Machine Learning, the classification becomes more accurate, being performed into smaller and smaller groups. This may include subgroups that had not been previously identified, and the quality of the service improves as it is thoroughly customised to the individual customer. This enables customers to enjoy a better experience as consumers, which makes them happier, and in turn, improves the profitability of the business.
Machine Learning and Deep Learning are leading the way for technological innovation in all fields, with great impact on the tourism sector. The potential of these processes is very promising. There is no doubt they can change diametrically the forms of commercialisation and the way the travel industry works.
You will find the reference information in Medium.