MABRIAN TECHNOLOGIES CALLS FOR THE END OF “BIG DATA” IN THE TOURISM SECTOR
While big data has revolutionised the tourism sector, Spanish company Mabrian Technologies says it’s calling for a change of tack, urging the sector to instead focus on actionable insights when looking at destination trends.
To help its partners achieve this, Mabrian has recently restructured its team, which works closely with businesses to help turn multiple data sources into specific information in the form of actionable insights.
Carlos Cendra, Sales & Marketing Director at Mabrian Technologies, says the company does this by providing clients with customised assessment to better understand their business needs and find the best information and indicators available to support their decisions.
“Our objective is clear: to move from providing you with information to providing you with answers,” said Mr Cendra. “To achieve that a balance between a powerful Travel Intelligence tool and a deep tourism sector knowledge is required. The sector needs agile solutions more than ever. To lead the Customer Success team we’ve recruited Sonia Huerta (eds: pictured above), who has more than 10 years of expertise in international projects, from THR Innovative Tourism Advisors, a management consultancy specialising in the tourism sector.”
Based in the Barcelona office of Mabrian Technologies, Ms Huerta will have a team of up to 20 people reporting directly to her by the end of 2021.
“There’s certainly been a bubble around ‘Big data’,” added Cendra. “Data is drowning tourism professionals and the last thing a drowning person needs is more water. Instead what people require is information that matters in the form of actionable insights taken from a choice selection of multiple data sources that are right for them – and this is why we have incorporated more tourism knowledge into our team, to better understand the challenges that our clients face daily.”
Mabrian Technologies debuts Natural Language Processing
Mr Cendra says people might be forgiven for not being familiar with the term “Natural Language Processing”, but as strengths go, it is one of the most relevant for the tourism sector.
“Kind of like in science fiction movies when someone can read minds, NLP is a technique that allows us to extract raw and unstructured data from sources such as social media and review platforms,” Cendra said. “We do this to listen in on conversations about your destination on social media and clean up that information into actionable insights: five indices that measure the performance (or satisfaction level) in all the main aspects of the destination and compare it with your competitors. All at a source-market-by-source-market level.”
The first of these indices is the Global Tourism Perception Index, which measures the overall level of satisfaction of visitors and is calculated by looking at the other four indices. Others include the Perception of Security Index, which looks at the perception that visitors from different countries have of security in that destination; a Perception of Climate Index measures the level of satisfaction that visitors have of the weather and overall climate – and reflects the relationship between the expectations and reality of visitors’ experiences.
A Tourism Product Index looks at how satisfied visitors are with the in-destination experiences such as gastronomy, nightlife, outdoors activities or shopping; the Hotel Satisfaction Index and that examines satisfaction levels of visitors staying in three, four and five star hotels – and is based on reviews left of sites such as Trip Advisor or Expedia.
“Natural Language Processing draws on machine learning and artificial intelligence (AI) to take data and segment by sentences, stemming (reducing words down to their origin), grammar labelling and other methods – all the while using special algorithms to exclude irrelevant data (particularly non-tourism related data),” concluded Mr Cendra.
Mabrian Technologies offers Natural Language Processing in English, Spanish, Catalan, Portuguese, Italian, French, German, Japanese and Russian.