Summer tourist trends 2021
Mabrian Technologies, presented – at a joint press conference held with Oliver Wyman under the theme of ‘Mega Trends in Travel’ – a real-time study about the behaviour of travellers during 2021 summer.
Tourist Intelligence
Data is not the answer
Carlos Cendra, Marketing & Sales Director at Mabrian Technologies, gave a lecture about globalizing the use of ‘Big Data’ analytics in the tourism sector and decision-making based on actionable insights.
Change of trend in Mediterranean hotel prices
Change of trend in Mediterranean hotel prices
Has the UK ‘staycation’ come to stay?
Study based on Mabrian Travel Intelligence Platform to analyse the current dynamics on domestic travel in the UK.
Introducing NLP
What’s your tourism strength? Ours is natural language processing, or as we call it: NLP.
The end of ‘big data’? Less is the new more in tourism now
Big data has revolutionised the way we live and operate in the tourism sector. But has big data become just a little bit too ‘big’? Do you find yourself dreaming of having just a little ‘less’ data to analyse?
The strength of demand to visit a destination: the Share of Searches Index
To identify the best recovery opportunities, once restrictions are lifted, Mabrian Technologies offers an indicator to measure the relative demand level from any source market to a destination.
Remote working has an impact on travel search trends
Flight searches during weekends and Mondays gain relevance as we attend the office less.
Main tourist trends in the Covid-19 era
The COVID-19 pandemic. On a global scale, the pandemic has precipitated tectonic shifts for society, politics and the world economy, highlighting the need to redefine how and when decisions are made and with what background information.
Perception of Security Index
Mabrian Technologies, a pioneer in the Travel Intelligence sector, has been working with this index for over four years to identify tourist trends associated with the confidence factor, in parallel to hundreds of other indicators calculated in real-time.