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Big data, big learnings

The term Big data often leads to big expectations: with these data the ultimate insight into consumer behaviour would arise. Large companies already collect a lot of data about their customers. With these "big data" patterns of interest are mapped out and new products and services developed. But such data analyses are not easy for SMEs. Every entrepreneur only sees a customer's visit to his own company, but he doesn’t know what the same customer does at other companies. And exactly that is essential in tourism: a guest usually does not visit a region because of a single company, but because of the combination of accommodation, restaurants, shops, attractions, landscape, transport, et cetera. In order to gain insight into behavioural patterns and interests of guests, it is necessary to gather data from multiple entrepreneurs and other sources and to analyse it in conjunction at destination level. That was the ambition of the big data activities in PROFIT. What are the opportunities for tourism SMEs? This was the central question during all kinds of data experiments in PROFIT. Some experiments led to very useful insights, others led to information of little relevance. All learnings have been brought together in one report

Cover PROFIT big data experiments

PROFITing from big data?

In PROFIT, there were five regions with different objectives and related issues. Moreover, the parties involved in these regions had very different levels of knowledge with regard to research and data analysis. Because of this complex starting situation and the difficult access to relevant data sets, it was especially important to gain knowledge about the possibilities and impossibilities with regard to big data in tourism SMEs. Many entrepreneurs initially thought that "big data" was not for them, but now realize that the data that they already possess can already offer many valuable insights for their own business operations. It is therefore important to make companies aware of the possibilities as much as possible, so that they can apply them in their own company, but also make them accessible for building knowledge at destination level.

With the results of the data experiments in PROFIT, there is a growing insight that big data can have added value for tourism businesses as well as destinations. To create valuable insights at the destination level, it is not sufficient to rely on data that are accessible here and there. To be able to actually build insights at destination level, businesses, public authorities and other stakeholders must work together to uniformly record and unlock the data from their own organisational processes. In this way, the necessary big data finally emerges for the issues that were formulated at the start of this project. By doing so, destinations can develop further into a situation in which data analyses help to describe, understand and predict consumer behaviour.

 

Example of data analysis, based on reviews

Looking at the data available for all the participating regions, we initially focussed on the subject of motivation and appreciation. We have experimented with data obtained from review websites and social media, in order to see whether this data will provide us with usable information for the questions we have about visitor motivation and appreciation. A few dashboards are shown, based on Google reviews. These are images of the analyses produced and show the possibilities offered by analysing reviews.