Big data kills the guesswork in tourism

New predictive models allow to show tourist’s demand evolution a year ahead.

Flight planning; agreements between hoteliers and tour operators to reserve seats; hiring employees for the high season; food purchase… Every year, the tourism industry must make multiple decisions based on a simple premise: predict and guess what the tourists’ behaviour will be. Artificial Intelligence and Big Data  are taking action on the matter.

So far, the most used method to predict how the next season will go is to analyze the flight bookings for the next months or the flight searches.

Get to predict tourist dynamics is the great challenge. The problem is that this dynamic is very veering, because unexpected things happen such as attacks, political convulsions, etc.”, says Santi Camps, CEO and also founder of the Spanish company Mabrian Technologies.

However, Technology can help to understand these dynamics, predict changes and their consequences”, adds.

In this line, Mabrian has developed a predictive model based on behavior social indicators, that can show the tourist’s demand evolution a year ahead.

The system is based on the constant monitoring of thousands of mentions in social networks (Instagram and Twitter) related to travel, and that takes into account the users’ profiles, even using facial recognition to deduce whether they´re young or old.

“We can anticipate if a market will remain stable, increase or decrease for each destination”

This huge data volume is transformed into a series of indicators: security, hotel satisfaction, travel intention, etc. “With all these components, depending on how they vary, we can anticipate if a market will remain stable, increase or decrease for each destination”, says Santi Camps.

“Variations on security are key: if it stays stable, that part of the formula doesn´t affect, but if it falls a lot, you can anticipate that bookings will be affected”.

Real cases

This predictive model’s effectiveness has been proved in several cases. For example, in October 2017 it was anticipated that Egypt, Turkey and Tunisia would be once again tough competitors for Spain in the summer of 2018.

And it’s that Mabrian’s “Perceived Security Index” for these countries stabilized above 80 points (on a scale of 0 to 100), specially among German tourists.

In Cuba we can find another example: thanks to Barack Obama and the restoration of diplomatic relations with the USA, in 2016 there was a significant increase in hotel prices, which was attributed to the great interest that Cuba was arousing among American tourists.

Some European tour operators considered whether it would be worthwhile to maintain their operations on the island if the very strong price escalation continued.

However, the USA market was generating 38% of the mentions in social networks about tourism in Cuba, but only 8% of hotel reviews. Canada, on the other hand, generated 48% of the hotel reviews.

At the same time, the intention to travel to Cuba from Italy, United Kingdom, Spain or Argentina had also increased.

“The conclusion was that Travel demand from the US, alone, didn’t explain the rise in hotel prices and everything seemed to indicate that a call effect was being produced”.

In other words, tourists from other countries where rushing to Travel to Cuba “before it changed” due to the supposed massive arrival of Americans and, therefore, that year´s price boom was only a temporary effect.

This article has been published September’s HOSTELTUR magazine.

Published in Hosteltur by Xavier Canalis

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