Consumer Data Research and Census Enumeration

Talk Given at the ONS, 25/2/16

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
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/
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
12. http://esociety.publicprofiler.org/
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
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)
31. 75%
36. Internet User Classification: Work in Progress • National extent • Integration of multiple consumer data • Actual use / spend