News & Insights

Machine Learning Technologies for the Hospitality Industry

16/05/2017 15:35:00 (GMT)

The way we book our holidays has changed dramatically over the last decade. It used to be the case that the average consumer would either visit their local travel agent in person or simply book their holiday through the travel agent's website. Now however the way we arrange and book our holidays has moved beyond this and customers expect more. Today's customer may end up visiting 20 or 30 different websites on different devices looking for the best rates or features available before making a purchase.

Every day millions of data points are created when customers visit hotel websites and browse around them. Aggregating this data for analysis can highlight the path each customer took before making their purchase. Thus, presenting a hotelier with opportunity and revenue potential if they can access this information. Acquiring and processing all of the data necessary to gain this information is a complex task that would take many man hours to accomplish. This is where the realm of Big Data and Machine Learning can help.

The use of Machine Learning and other Artificial Intelligence technology has the ability to transform the hospitality industry and in many cases this has already begun. Traditional solutions tend to focus on the creation of static models that limit analysis through samples that are frozen in time. Using such an approach to help forecast the correlation between something such as prices and occupancy over time can result in unreliable conclusions. The hospitality industry is constantly moving and moving very fast. Therefore, any system that can be applied must share these features.

Some hotels are already early adopters of this type of approach with tedious tasks like pricing and demand forecasting already being processed by such systems running in the background and allowing revenue teams the time to focus on other areas of their jobs more effectively.

With the rise of platforms such as TripAdvisor and AirBnb, not only making it easier for consumers to compare competitors against one another but also, providing access to alternative accommodation categories hoteliers need to adopt new techniques to protect market share.

There are not many industries as consumer-centric as the hospitality industry with each type of business trying to create a valuable customer journey from start to finish. Harnessing the power of Artificial Intelligence and Machine Learning through powerful Data Science platforms can help create a more personalised view of each customer that can aid with engaging them on a deeper level than before.

Capturing information about customer purchases, location preferences, travel patterns and customer experience inquires can help increase the efficiency of the analytics being utilised and aid companies in the hospitality industry with meeting the increasing customer expectation as well as pivot when presented with new unforeseen issues.

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