Mobile phones are ubiquitous sensors of the society. Individually, these anonymous signals do not mean much but taken together they can be used to paint a picture of the streets. Carefully processed, this information can provide continuous data on various areas -- tourism, urban planning, transportation management.
Interested in national figures? Or a city district?
If the mobile operator's coverage reaches over the entire country, so does the data. Survey rural areas, national parks or zoom into cities within a block radius.
Residents are only part of the picture? Want to measure passers-through?
Everyone using the mobile network are covered - which includes tourists and persons in transit - places are now characterized more accurately based on all of the people there.
Want to survey over a long period? Missed a key event without doing a survey?
Anonymous data is collected over long periods of time allowing useful comparisons. Determine repeat visitors or behaviour over a time frame you choose without panel surveys or intruding on anyone's privacy.
The world has been taken over by mobile. The mobile phone has become the centerpoint of communication and daily life. It is only logical that travel behaviour is measured with that most common travel companion - through data generated by the mobile phone.
Location data from operators ensures the best information on visitors. Positium provides a report-based interactive monitoring tool that presents inbound (foreigners) and domestic (local tourists) tourism statistics on national as well as regional level.
How many tourists from the UK visited the national capital during a football match? What is the composition of tourists (by country) visiting a specific region? What is the average duration of a visit? Did the foreign tourism attraction campaign take effect? How do two different regions compare in the sense of tourism and their attractiveness?
This tool also answers a number of questions that are traditionally gathered by conducting expensive and short-term tourism surveys and by analysing usually inadequate accommodation statistics. Traditional data is used alongside data from mobile positioning making this the ultimate tourism statistics information centre for organisations that require this type of data.
Rely on information, not approximate numbers
Positium's usual environment model is 95% accurate at detecting home locations at even a municipality (LAU2) level.
Mobile positioning data shows the same trends as most supply and demand statistics, but also discovers pockets of tourism hidden from traditional sources.
At a fraction of the time it takes to gather indicators the traditional way.
Length of stay - Trips and legs of trips can be classified according to length of stay for the visitors, giving a better understanding of the behaviour of the tourist.
All visitors - Mobile data captures all visitors, including those not checked in to traditional accommodation establishments. Long-term and transit visitors can be excluded by behaviour. The result is a more accurate presentation of the state of tourism in the country or locality.
Ask us for a list of indicators.
Correlation analysis conducted by Statistics Finland concluded that mobile positioning data is very tightly correlated to important sources of supply and demand statistics (r mostly 0.9-1.0). I.e. the trends shown are similar.
Mobile positioning includes many tourists that traditional sources miss, such as those not staying at official accommodation establishments. That leads to higher figures than most traditional sources, as more forms of tourism are detected.
Larger sample size, less dropouts and fewer missing answers compared to surveys. Very little imputing necessary. Fewer measurement errors.
Thanks to a large amount of data, Positium's model determines home locations with up to 95% correct identification on the municipality level (LAU2) - very important for separating tourists from residents.
Updates are possible near real time through automation. A cost-efficient 15-day-period is usually sufficient, meeting most purposes. At the same time that is much faster than most accommodation statistics and survey data.
The data is already there, passively collected through normal use of the mobile device - without costly questionnaires or apps and the associated battery drain.
There is no burden on the tourists or any single person for that matter. No burden on the tourism industry (e.g. accommodation establishments). Mobile operators merely have to share the data they already collect.
We take privacy seriously, which is why we rely on strong encryption while transferring data (the same standard the US Government uses for top-secret level information). We also make sure no single person can be identified by third parties from our aggregated data.
For Statistical Offices, data is handled anonymously in accordance with Statistical Acts that apply.
There are more than 30 people in the Positium family, mostly coming from a social geography or geoinformation systems background. Combined the team has over 100 years of experience in analysing mobile positioning data for public planning, transportation, tourism. Researching location data and understanding people's activity spaces is our passion.
Margus is the CEO and Member of Board at Positium. He has an extensive background in geoinformatic systems (in which he holds an MSc degree) and data mining. He has been working with mobile positioning data for 8 years.
Margus also thoroughly enjoys a good game of chess.
Fields of specialization: geoinformatics (GIS), cartography, computer sciences, web-based GIS applications, position determining systems (GPS, MPS, WiFi fingerprinting, footprinting etc), mobile positioning technologies, large-scale spatio-temporal databases and data processing, data mining, navigation, tourism statistics, socio-economic aspects of human mobility.
Erki is the Chief Technical Officer and Member of the Board at Positium. He has an MSc in Geoinformatics and has 7 years of experience working with mobile positioning systems for operators across the globe.
Erki is the outdoorsy type.
Fields of specialization: geoinformatics (GIS), cartography, computer sciences, web-based GIS applications, position determining systems (GPS, MPS, WiFi fingerprinting, footprinting etc), mobile positioning technologies, data mining, navigation, time-spatial behaviour, time geography, urban geography, Location Based Services (LBS).
Rein is a research professor of human geography at the University of Tartu. He heads the lab of mobility studies at the University, which has spawned many frontier studies in the field of mobile positioning since 2004. Highly decorated and referenced in the academic world, Rein has 10 years of experience in research with mobile data in urban geography, tourism and mobility.
Contact Rein for academic matters.
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