1 / 36

Geodemographic Analysis

Claire M. Palmer GIS 3130 Advanced Spatial Analysis March 19, 2008. Geodemographic Analysis. Outline. What is Geodemographic Analysis? History Geodemographics today Case Studies Conclusion. What is Geodemographic Analysis?.

sukey
Download Presentation

Geodemographic Analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Claire M. Palmer GIS 3130 Advanced Spatial Analysis March 19, 2008 Geodemographic Analysis

  2. Outline What is Geodemographic Analysis? History Geodemographics today Case Studies Conclusion

  3. What is Geodemographic Analysis? 12 geodemographic “groups” or “neighborhoods” in Bristol, United Kingdom

  4. Geodemographics… The analysis of people by where they live (Sleight, 2004) Where you are says something about who you are Linking people to places

  5. Geodemographicsis based on two simple principles… Two people who live in the same area are more likely to have similar characteristics than two people selected at random 1.  

  6. Geodemographicsis based on two simple principles… 2. Two areas can be identified in terms of the characteristics of the populace they contain, using demographics and other measures. Geographical areas can then be placed in the same segment even though they are geographically distant 

  7. Geodemographics… • Analysis of socio-economic and behavioral data about people • Investigates the geographical patterns that are structured by the forms and functions of settlements • Efficient discriminator of consumer behaviors and aids market analysis • Effective predictive tool for decision support

  8. Where did this concept come from?

  9. TOBLER’S LAW: Things near each other are more alikethan things far apart The ESRI Guide to GIS Analysis, Volume 2 p. 104

  10. TOBLER’S LAW: (examples) • Climate of nearby areas • House values • High crop yields of neighboring farms(same soil characteristics) • Ethnic communities within cities tend to settle in same neighborhoods (relatives and others of same ethnicity tend to live near each other) The ESRI Guide to GIS Analysis, Volume 2 p. 104

  11. TOBLER’S LAW: (exceptions) • Climate of two cities far apart on one side of a mountain are more similar than to a closer city on the other side of a mountain range • Neighborhoods can change abruptly if separated by a highway or a river The ESRI Guide to GIS Analysis, Volume 2 p. 104

  12. Geodemographic Analysis is not new!

  13. Chicago School of Urban Sociologists1920-1930 Concentric Zone Theory (1925) Ernest W. Burgess (1886-1966) Robert E. Park (1864-1944)

  14. Concentric Zone Theory(1925) Concentric zone theory was one of the earliest models developed to explain the spatial organization of urban areas. • maps social problems such as unemployment and crime in certain districts • reveals the spatial distribution of social problems and permits comparison between areas

  15. Present-dayGeodemographic Analysis

  16. Geodemographics today… • Cluster Analysis (Bailey & Tyron, 1970) – four decades of census data & election results in the SF Bay Area revealed that the aggregate political behavior of the tracts stayed the same • rapid growth in the amount of geographic information collected about people and places • geographic information handling technologies such as GIS • development of Geodemographic (GD) classification systems

  17. Geodemographic classification systems…characteristics • Private sector household-level databases prove more relevant than census data • Cluster analysis to identify similar neighborhoods • Three dimensions to households: 1) life-cycle needs2) buying power 3) spending power

  18. Geodemographic classification systems…uses Business • Retail Management / Market Analysis • Site Location – where’s the best places to open/close/re-brand • Target Marketing – who are my prospects and where can I find them? • Media Analysis – which Newspapers/TV stations/Radio/Web sites are most cost effective? • Market Size Estimation – what is the local market size for my product/service • Recruitment & Retention – which customers are most like to stay/churn Government • Resource Allocation / Facility Planning • Health, education, law enforcement, social regeneration • Justify the appropriateness for sought allocation

  19. Commercially available GD systems... USA UK Claritas • 62 clusters define eachneighborhood in the US • 15 social groups within each cluster, by the degree of urbanization ACORN AClassification Of Residential Neighborhoods

  20. Mosaic interface...

  21. Case Study:Geodemographics & Recycling in Surrey, UK • Evaluate demographic and geographic factors in recycling motivation • Survey households (2 urban, 2 rural) rural study zones: Middle Burne (deprived) Upper Hale (least deprived) urban study zones: Worcester Park (deprived) Longmead Estates (least deprived)

  22. Case Study:Geodemographics & Recycling in Surrey, UK • ArcGIS Network Analyst for road networks

  23. Case Study:Geodemographics & Recycling in Surrey, UK

  24. Case Study:Geodemographics & Recycling in Surrey, UK

  25. Case Study:Geodemographics & Recycling in Surrey, UK Findings • higher recycling in affluent zones • retired residents recycled most • People in rural areas travel further to recycle but travel time was not significantly different between urban and rural groups • People in urban areas tend to seek out the nearest bring-site whilst those in rural areas choose more of a variety

  26. Case Study:Geodemographics & the Financial Service Industry in the UK GIS & geodemographics for a competitive edge • Profiling & finding customers • Credit scoring • Branch location • Fuzzy geodemographics

  27. Case Study:GD & the Financial Service Industry in the UK Profiling & finding customers • Produce a list of account holders of various types (current account, mortgages, savings, etc.) • Assign account holder to a census tract by their address • Use the GIS to find new customers by searching for areas that contain the same geodemographic mix as the existing customer profile, preferably where existing market share is low Overlay

  28. Case Study:GD & the Financial Service Industry in the UK Credit Scoring • Increased cases of bad debt • One response to this phenomenon has been for many banks to close branches in less affluent parts of U.K. cities • Geodemographics could be used to identify potential market areas where mortgages and loans might be more difficult to recover • Consumers could be rated on the likelihood of their ability to repay based on existing knowledge of the geodemographics of past defaulters Overlay

  29. Case Study:GD & the Financial Service Industry in the UK Branch Location

  30. Case Study:GD & the Financial Service Industry in the UK Customer Profiling & Fuzzy Geodemographics • Geodemographic products are general purpose systems with often limited data sets • ‘‘Smarter’’ (or ‘‘fuzzy’’) geodemographic systems are not as reliant on the usual single descriptor • Fuzziness in attribute space – a locality may differ by only a very small amount in the geodemographic classification from its neighbors but still be assigned to a very different cluster • Fuzziness in geographical space – ecological fallacy problem and/or MAUP. Two neighboring census tracts may have very different classifications, but often people who live in neighboring tracts still demonstrate characteristics and economic behavior similar to that of their neighbors Solution Display all clusters, esp., clusters similar to dominant cluster

  31. Case Study:GD & the Financial Service Industry in the UK Customer Profiling & Fuzzy Geodemographics

  32. Case Study:GD & the Financial Service Industry in the UK Summary • GIS is a useful support tool for geodemographics – data storage and display, overlay of non-census data • Key target groups can be identified, enabling focused marketing and credit scoring • Buffer & overlay analysis key for catchment area analysis

  33. Conclusions / Critiques Geodemographic data is more robust than census data (lifestyles & behaviors) GIS is a useful support tool for geodemographics BUT… Problem of decay & inaccurate data Represents relatively crude averages of the population Ecological fallacy (the fallacy of homogeneity across the neighborhood) "The 'strategic intent' of geodemographic systems is replete with metaphors of vision, insight, omniscience, prediction, manipulation, and control. " (Pickles, 1994) Concern for individual privacy rights Serendipity factor lost?

  34. Thanks for your patience! comments or tomatoes welcome

More Related