1. Building a tourism intelligence system using big data Jon Kepa Gerrikagoitia, Ph.D. OPTIMA / Optimization Modelling & Analytics ICT - European Software Institute Division jonkepa.gerrikagoitia@tecnalia.com Aurkene Alzua Sorzabal, Ph.D. CICtourGUNE AurkeneAlzua@tourgune.org

2. The importance of tourism worldwide UNWTO (2014) Tourism is an economic phenomenon concerning the movement of people to places outside their usual environment for either personal or professional purposes. Great impact of tourism on the economy (employment, income): need for detailed and updated information in “real time” GDP employment

3. Our challenge 3 Incorporate new measurement methods based on digital footprint (Big Data) as an alternative and complementary source in the statistical production Why: Efficiency (cost, time) How : Tourism Observatory as intelligence platform in tourism to leverage innovative business models based on data economy

4. 4 The Relationship between statistics and technology Tourism Observatories – conceptual framework

5. Tourism Observatories –sources and methods

6. Tourism Observatories – technology

7. Tourism Observatories – types of analytics

8. 8 Dynamic Pricing monitor - Big data and its uses in the tourism statistics Official figures are published with a delay up to weeks. The system can publish the data at the end of the collection period (for example the last day of the month) Good fit and strong correlation between pricing official statistics and the monitor’s data. Difference aprox. 5% Modelling and prediction of hotel occupancy rates based on room prices offered online Dynamic pricing patterns and impact

9. Hotel occupancy estimates at subnational level, Basque Country (Spain) 9 For each hotel, three percentiles (P 30, P 70, and P 99 ) have been used as the bounds: Seg1 low prices Seg2 normal or middle prices Seg3 high prices Seg4 unusually high prices Fitted linear regression model Model stimates and residuals Data: 1.984.149 observations for the Basque Country from 2013-01-01 to 2013-12-31 Method: The system collects double room price 1,..., 28, 45, 60, and 90 days in advance of the target date. Results: Dynamic Pricing monitor - Big data and its uses in the tourism statistics

10. Occupancy prediction model at subnational level, Basque Country (Spain) 10 Predictions for the Basque Country for 2014 Model that allows to predict occupancy rates before the official figures are available Segmentation bounds obtained for the 2013 data (training set) and model are applied to data for 2014 (test set) Dynamic Pricing monitor - Big data and its uses in the tourism statistics

11. 11 Price, seasonality and trend Spain, Basque Contry, San Sebastian and Rioja in 2014 Dynamic Pricing monitor - Big data and its uses in the tourism statistics

12. 12 Destination performance analysis - Bilbao Dynamic Pricing monitor - Big data and its uses in the tourism statistics

13. 13 Benchmarking Regions in Spain Dynamic Pricing monitor - Big data and its uses in the tourism statistics

14. 14 Benchmarking Regions in Europe (France, Spain, Ireland) Dynamic Pricing monitor - Big data and its uses in the tourism statistics

15. 15 Dynamic Pricing monitor – Benchmarking Countries (France, Spain, Ireland)

16. 16 Dynamic Pricing monitor Benchmarking cities (Bilbao, San Sebastian, Vitoria) June – September 2013 June – September 2014

17. 17 Informal accommodation monitoring - Airbnb - July 2015 Apartment - w (N=622) Private room - p (N=437) ArabaBizkaiaGipuzkoa room3554,160,2 apartment130119173,5 Mean price (€) airbnb offer in july in the Basque Country Dynamic Pricing monitor - Big data and its uses in the tourism statistics

18. Monitoring platform and active listening in social media that allows Learn and discover: what (concepts) - how (polarity) - where (sources of opinion) and management: early warning, real-time monitoring online reputation using language processing technologies, visualization and analytical modeling It has been applied in the fields of Tourism, Culture, Territory, Transport and Innovation models. Social Media Monitor

19. Destination Image Framework

20. Results

22. Destination Web Monitor Destination Web Monitor (DWM) is “a system to measure, analyse, and model the behaviour of visitors in different virtual areas in which a destination is promoted and with the objective of providing benchmarking ratios that facilitate strategic surveillance and intelligent marketing policies”

23. Descriptive analysis Navigation patterns Typologies Destination Web Monitor

24. Thank you ! Eskerrik asko! Muchas gracias ! Jon Kepa Gerrikagoitia, Ph.D. OPTIMA / Optimization Modelling & Analytics ICT - European Software Institute Division jonkepa.gerrikagoitia@tecnalia.com Aurkene Alzua Sorzabal, Ph.D. CICtourGUNE AurkeneAlzua@tourgune.org