As we all know the hospitality industry is a highly customer centered business and it is gathering large amounts of data daily from their central reservation systems (CRS), property management system (PMS), point-of-sale (POS), and guest loyalty program databases. As you might have expected using data mining efficiently in this field plays a huge role in formulating marketing strategies, enhance guest experiences, increase retention and loyalty and ultimately, maximize profits.
Methods of finding interesting patterns and structures in a large database, an automated process of “mining” through unstructured data.
A copy of the organizational data specifically organized for analysis and reporting. In the hospitality industry for example we collect a lot of data from our guests, employees and vendors.
For a better understanding of the data mining process, we have a series of 7 steps that need to be implemented:
The goals of data mining is to be able to predict what the customers want and to eventually optimize the offered services in order to reach their expectations and desires, eventually reaching great customer satisfaction levels.
Is one of the data mining techniques that works with large volumes of textual information in order to discover underlying patterns in the studied text. The text mining technique is used while analyzing online reviews, from platforms such as HollidayCheck and TripAdvisor.
Usually data mining requires a lot of manual work, but of course there are different software that can help out in sorting through the data and organizing it for you, making it accessible and ready to use. But just in case, here are some guidelines for an effective management of data-mining technology:
Without data mining valuable information about your guests can be lost or overseen, success or failure depends not only on how well you are able to collect this data but also how good you are at converting it into useful information.