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Geodemographic Profiling, Knowledge Workers and Networks

This article explores the concept of geodemographic profiling, highlighting its historical roots with Charles Booth's work on London poverty mapping and the Chicago School's contributions. It discusses contemporary applications in the commercial sector via tools like MOSAIC, which classifies neighborhoods based on demographic data. The progression from raw data to actionable intelligence in a digital networked society is examined, emphasizing the importance of understanding cultural, ethnic, and linguistic factors in data profiling. The implications for knowledge workers and targeting communications are significant as society navigates the digital divide.

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Geodemographic Profiling, Knowledge Workers and Networks

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  1. Geodemographic Profiling,Knowledge Workers and Networks Dr Tom Williamson Visiting Professor Institute of Criminal Justice Studies University of Portsmouth

  2. Geodemographic Profiling • Charles Booth: 19th Century industrialist turned social scientist • Profiled all homes in London: 5 broad groups • 30.7% below the poverty line • Descriptive map of London Poverty 1889 • http://booth.lse.ac.uk/ • Chicago School. Park Burgess and McKenzie 1925. Lost until rediscovered by the commercial sector in 1980s. • Cf. Harris, R., Sleight, P., Webber, R. (2005) Geodemographics, GIS and Neighbourhood Targeting. Wiley.

  3. Importance of Neighbourhood context • Geodemographic software MOSAIC. 11 broad neighbourhood groups 61 smaller types. • Built from census, commercial transaction and survey data to provide the neighbourhood profile. • Massive amount of data or is it ‘knowledge’.

  4. Knowledge • ‘Knowledge is the sum of what is known to mankind’ OED

  5. Progression towards knowledge. • Data. • Information. Analysis of data provides information • Intelligence is information prepared for action • Intelligence acted upon provides experience • Experience contributes to our knowledge and understanding and allows us to test hypotheses

  6. Networks and the digital divide • Between traditional manual systems and the ever-widening influence of ICT networks. • The ‘Future is Digital’. • Wrong!, digital will be a given in the 21st Century. We will live in a networked society. Transactions and travel captured digitally. • ICT automatically captures data. The Future is Data. Combine harvesters. Data aggregators. • Google type technologies together with analytical tools means we are all becoming ‘knowledge workers’ processing the digital harvest.

  7. Widely used in the commercial sectorSite location

  8. Segmenting customers: Targeting of communications

  9. Perceptions of local crime rate A B C D E F G H I J K

  10. Walton North ward (NE corner)

  11. Low level of social cohesion

  12. Most prevalent Index profiles

  13. Community coding of Electoral Register • 46,330,000 records on file • 99.1% coded by community of origin • 130 Cultural, Ethnic, Linguistic CEL types • 13 Cultural, Ethnic, Linguistic CEL groups

  14. Coverage

  15. The following maps are created in a novel way • 1 : We have examined a UK database containing 46 million records. Each contains personal name + family name + postcode • 2 : We have classified 180,000 family names and 100,000 personal names on the basis of ethnicity, loosely defined • 3 : Using these tables we have coded 99.3% of the 46 million records according to their most likely ‘cultural/ethnic/linguistic group’ • 4 : We have then selected the 60,000 UK postcodes containing 7 or more individuals identified as belonging to a group which is neither British nor Irish • 5 : The postcodes have then been coloured according to the group with the highest number of names in the postcode. • 6 : One of the maps shows the distribution of all major groups within Greater London. • 7 : The other map features the largest of just three groups in Birmingham and the Black Country • 8 : In the Black Country map there is a green background behind each postcode. The strength of the green colouring indicates the proportion of the population in the postcode with a South Asian name. Thus the map shows both the level of concentration of South Asian names in a postcode and which of the minority groups is most strongly represented.

  16. Black Country : dominant names by postcodeBlue = Sikh, Yellow = Pakistani, Red = Hindu

  17. The ethnic map of London R. Webber

  18. Hackney

  19. Brent

  20. Health communications : Camden PCT

  21. Residential segregation : selected Local Authorities

  22. Ethnic and religious profiling • Legal in the UK • Ethnic marketing is a growing business • Public sector applications?

  23. Conclusions • ICT Networks will become increasingly pervasive in 21st Century • Knowledge no longer in the hands of the ‘police’ or ‘police officers’. Consumers of knowledge. • Geodemographic, cultural, ethnic and language profiling will become easily accessible. • Challenge is whether we buy into this ‘knowledge’ as a new way of doing business or continue ignoring it.

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