The size of the transient population is growing everywhere: more people travel, more people extend their travel reach and more economic activities depend on the transient population. Be it for tourism or for business, our economies depend more and more on the choices, flows and patterns of these people.
But how much do we know about this phenomenon locally and globally? What influences the decisions to travel to a certain destination? Where do tourists come from, where do they stay, where will they go next? After their visit, do they become promoters of the destination? Who will visit which place in the future?
While official statistics provide ample evidence of the main facts and trends of the transient population, the granularity, specificity and resolution of the information available is almost always insufficient to inform the vast majority of decisions of private and public actors. Besides, it is a mirror view: we measure what has taken place and have very little guidance on the future.
This was understandable when the costs and complexity of gathering high-resolution facts were so high that the business logic of doing so was hard to justify. Research and experimentation on collective sensing for measuring, categorizing and predicting large-scale human patterns has changed all that. Combined with the availability of massive amounts of data from social media, web activity, telecom traffic, payments or urban sensors we have an opportunity for a far better, more precise and informative visibility on the transient populations.
Without impinging on personal privacy, we believe Data Science and Big Data can disrupt the way we create policies and manage tourism, from the global to the local levels, for the public and private sectors.
New data sources provide the proxies for measuring, understanding and predicting the transient population experience: from the choice of where and when to go, to the local choices of places and activities, to the way we share our experience afterwards. Data science and predictive analytics provide the tools to extract value from this data and inform policy makers and decision makers.
> What do they search for?
> Who are the network centers?
> What influences the choices?
> Where do they come from?
> Where do they go?
> How do they travel?
> How much do they spend?
> How long do they stay?
> Ho do they talk about their experience?
> What inspired their visit?
> Will they be promoters?
> Will they be detractors?
New data sources, such as Telecom transaction, payment transactions or social media provide proxies for understanding intention, choice, visit and feedback.
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