Consumer Data Research and Census Enumeration

Transcript

1. www.alex-singleton.com @alexsingleton Consumer Data Research Centre An ESRC Data Investment

   Professor Alex Singleton Department of Geography and Planning, University of Liverpool Consumer Data Research and Census Enumeration

2. Consumer Data Research Centre An ESRC Data Investment

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4. http://maps.cdrc.ac.uk/#/geodemographics/iuc14/default/BTTTFTT/12/-1.8265/50.7308/ http://data.cdrc.ac.uk

5. https://www.flickr.com/photos/ bluesquarething/5512923662/

6. http://www.alex-singleton.com/r/2014/02/05/2011-census-open-atlas-project-version-two/

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8. “What is needed is a solution which will pick out

   pattern from the detail, without loosing too much of the original information, and which will admit more detailed examination of parts of the pattern which become relevant to a particular issue or local area as and when required” Webber (1978, 275).

9. http://www.google.co.uk/intl/en_uk/earth/ how?

10. http://www.google.co.uk/intl/en_uk/earth/ 52: POORER FAMILIES, MANY CHILDREN, TERRACED HOUSING 51: YOUNG

    PEOPLE IN SMALL, LOW COST TERRACES 59: DEPRIVED AREAS AND HIGH- RISE FLATS 11: SETTLED SUBURBIA, OLDER PEOPLE Urban Adversity Affluent Achievers
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12. http://esociety.publicprofiler.org/

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14. http://esociety.publicprofiler.org/ 250k views - afternoon released

15. Postcode Search Propensity by e-Society Types 0" 20" 40" 60"

    80" 100" 120" 140" 160" 180" 200" 220" 240" 260" 280" 300" Index"(Base"100)" Group"A":"E;unengaged" Group"B":"E;marginalised" Group"C":"Becoming"engaged" Group"D":"E"for"entertainment"&" shopping" Group"E":"E;independents" Group"F":"Instrumental"E;users" Group"G":"E;business"users" Group"H":"E;"experts"

16. Feedback Origin 0" 20" 40" 60" 80" 100" 120" 140"

    160" 180" 200" 220" 240" Index"(Base"100)" Group"A":"E:unengaged" Group"B":"E:marginalised" Group"C":"Becoming"engaged" Group"D":"E"for"entertainment"&" shopping" Group"E":"E:independents" Group"F":"Instrumental"E:users" Group"G":"E:business"users" Group"H":"E:"experts"

17. Feedback Destination 0" 50" 100" 150" 200" 250" 300" 350"

    400" 450" 500" Index"(Base"100)" Group"A":"E:unengaged" Group"B":"E:marginalised" Group"C":"Becoming"engaged" Group"D":"E"for"entertainment"&" shopping" Group"E":"E:independents" Group"F":"Instrumental"E:users" Group"G":"E:business"users" Group"H":"E:"experts"

18. Distance to telephone exchange

19. Distance to mobile mast http://sitefinder.ofcom.org.uk/ http://www.sharegeo.ac.uk/handle/10672/372

20. Download Speeds

21. % households with Internet connection

22. % of people who mostly use mobile phone for internet

    access

23. % Students

24. Internet User Classification

25. An application in retail… • To what extent are retail

    centres exposed to populations with variable engagement in online retail
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27. What do you need to know? • Estimate of those

    people likely to visit a retail centre • Influences on the level and type of engagement of such populations • The composition of the retail centre

28. Online&sales& Supply&factors& Demand&factors& Retail/Service& Offer& Catchments& &Demographics& Retail& e<Resilience& Vulnerability/adapta?on&

    Connec?vity& Consumer&Behaviour& retail/service+mix+ +++a.rac/veness++ +++++shopping+convenience++ + + socio5economic+status+ age+ + ++infrastructure+ +++++++speed+ rurality+ Engagement+with+ICT+ ++++++Shopping+online+ +

29. Catchment Estimates LSOA (i) A - attractiveness D - distance

    Retail Centre (j) L LDC Pij = A↵ j D sj ij Pn j=1 A↵ j D sj ij Large, Medium, Small (s)
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31. 75%

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36. Internet User Classification: Work in Progress • National extent •

    Integration of multiple consumer data • Actual use / spend