European neighbourhood in a few figures

Transcription

1 European neighbourhood in a few figures

2 ? Why are we here? Discover the world of data The neighbourhood identity Mobile data analysis Closing thoughts

3 European neighbourhood Identity card People Touristic Attractiveness Mobility Sources

4 People

5 International area with high revenue 2,367 Inhabitants (49% Women 51% Men) 11,98% Unemployment rate (VS 22.69% regional average) Median revenue 23,856 (VS 18,941 regional average) 68% foreigners (83% European 17% Rest of the World) average household size: 1.52 average age (years): 37.66

6 Touristic attractiveness

7 Variety of museums ,889 Monthly affluence to attractions & museums Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Nationality of the visitors: 23% 15 % & 11% Average from Jan to Aug Data by nationality according to Brussels Cards figures, from Jan. to Aug. 2017

8 Top range accommodation 67.6% Hotels occupancy rate 69.3% Regional average 13 hotels 2500 rooms Average from Jan to Jul. 2017

9 and alternatives AirBnB lodgings Average price Regional average Hotels Average price Regional average

10 Attractive touristic offer 3 Restaurants In Michelin guide (2017) 27 Bar & Pubs recorded on Yelp 5 Touristic sites in Michelin guide (2017) 1 *** (Natural Sciences Museum) 47 Shops recorded on Yelp

11 Diversity of venues 250 to 1000 persons 12 Meeting rooms Up to 250 persons 100 Meeting rooms Source: Let s Meet 2017 (extended area: EU + Cinquantenaire).

12 Mobility

13 Great accessibility People live close to % a bus stop (<250m) 74% regional average 83% a metro station (<500m) 30% regional average 0% a tramway stop (<400m) 64% regional average Source: IBSA

14 and other green solutions Villo stations Bike stands 4 Electric charging stations 10 Cars capacity Source: Open Data Store

15 Sources of information

16 Where can you find this information? 1 Tourism Barometer 2 Monitoring des quartiers 3 Other sources Guide Michelin Inside AirBnB CIRB Open Data Yelp

17 Mobile Data Analysis

18 1 Introduction

19 Methodology Sim cards movements tracking Specific area (12 cells) 1 hour at the departure & arrival

20 Statistical zone Cells coverage 1 month data Hourly report Origin & destination Monitoring by cell Excluding holidays

21 Zone 1 Parc Léopold & Place Jean Rey

22 Zone 2 DG Energy

23 Zone 3 Berlaymont & Schuman

24 Zone 4 Maelbeek & Loi

25 Zone 5 Committee of the regions & Concert Noble

26 Zone 6 European Parliament & Natural Sciences

27 Zone 7 German embassy, Thon & Chinese cultural center

28 Zone 8 DG migration & Square de Meeus

29 Zone 9 Luxembourg Square & Station

30 Zone 10 St Joseph Church, DG IT

31 Zone 11 Orban square & Total

32 Zone 12 Trone

33 Average hourly movements :00 01:00 01:00 02:00 02:00 03:00 03:00 04:00 04:00 05:00 05:00 06:00 06:00 07:00 07:00 08:00 08:00 09:00 09:00 10:00 10:00 11:00 11:00 12:00 12:00 13:00 13:00 14:00 14:00 15:00 15:00 16:00 16:00 17:00 17:00 18:00 18:00 19:00 19:00 20:00 20:00 21:00 21:00 22:00 22:00 23:00 23:00 00:00 To the area Within area

34 2 Incoming Journeys

35 Journeys by destination (daily average) Monday 1 Berlaymont Tuesday 1 Berlaymont Thursday 1 Berlaymont 2 Orban Square 2 European Parliament 2 European Parliament 3 European Parliament 3 Orban Square 3 Orban Square 4 Leopold Square 4 Luxembourg 4 Luxembourg 5 Luxembourg 5 Maelbeek & Lois 5 Leopold Square

36 Journeys by source (daily average) 80% 70% 69% 60% 50% 40% 30% 20% 10% 0% 16% 11% 2% 1% Brussels Rest of Flanders Rest of Wallonia Brabant (WL+FL) Abroad 25% 20% Other Brussels 15% 10% 5% 0% 00:00 01:00 01:00 02:00 02:00 03:00 03:00 04:00 04:00 05:00 05:00 06:00 06:00 07:00 07:00 08:00 08:00 09:00 09:00 10:00 10:00 11:00 11:00 12:00 12:00 13:00 13:00 14:00 14:00 15:00 15:00 16:00 16:00 17:00 17:00 18:00 18:00 19:00 19:00 20:00 20:00 21:00 21:00 22:00 22:00 23:00 23:00 00:00

37 3 Internal Journeys

38 Biggest internal flows (top 10) DG Energy Leopold 6 Leopold Berlaymond 2 Parliament Luxembourg 7 Comittee of regions Leopold 3 Parliament Leopold 8 Square de Meeus Luxembourg 4 DG Energy Berlaymont 9 Comittee of regions Luxemborg 5 Maelbeek Berlaymont 10 Comittee of regions Parliament

39 Closing thoughts

40 Analytics is not a complicated thing

41 A lot of data sources are available Data from operations Data from field research Data from open sources Data from communication Data from paid sources

42 Efficient tools are not always expensive Non exhaustive list of free solutions + Nice design Complete toolbox + Close to Excel Included in O365 + Powerful data engine Save only online Only on files Still in development Microsoft Less modern design + Very easy to use Set of powerful models + A very complete library Open source Black box Limited library Requires coding

43 Try new analyses Data reporting Data classification Data forecasting What has been my last month performance? How satisfied were my clients with my services? What are the segments in my clients base? In which segment should I categorize a new client? What will be my performance in the next year? Which clients are the most likely to buy a new product?

44 Be creative

45 Contacts Simon Detemmerman Corentin Descamps > Pro & Press > Observatory