claire m. palmer gis 3130 advanced spatial analysis march 19, 2008 geodemographic analysis

Claire M. PalmerGIS 3130 Advanced Spatial Analysis

March 19, 2008

Geodemographic Analysis

Outline

What is Geodemographic Analysis? History Geodemographics today Case Studies Conclusion

What is Geodemographic Analysis?

12 geodemographic “groups” or “neighborhoods” in Bristol, United Kingdom

Geodemographics…

The analysis of people by where they live

(Sleight, 2004)

Where you are says something about who you are

Linking people to places

Two people who live in the same area are more likely to have similar characteristics than two people selected at random

1.

Geodemographicsis based on two simple principles…

Geodemographicsis based on two simple principles…

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

2.

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

Where did this concept come from

?

Things near each other are more alikethan things far apart

The ESRI Guide to GIS Analysis, Volume 2 p. 104

TOBLER’S LAW:

(examples)

Climate of nearby areas


TOBLER’S LAW:

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)

(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


TOBLER’S LAW:

Neighborhoods can change abruptly if separated by a highway or a river

Geodemographic Analysis is not new!

Chicago School of Urban Sociologists1920-1930

Ernest W. Burgess (1886-1966)

Robert E. Park (1864-1944)

Concentric Zone Theory (1925)

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

Present-dayGeodemographic Analysis

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

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

Geodemographic classification systems…uses

Retail Management / Market Analysis

Resource Allocation / Facility Planning

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

Business

Government

Health, education, law enforcement, social regeneration Justify the appropriateness for sought allocation

Claritas

Commercially available GD systems...

USA UK

62 clusters define eachneighborhood in the US

15 social groups within each cluster, by the degree of urbanization

ACORNA Classification Of Residential Neighborhoods

Mosaic interface...

Case Study:

Geodemographics & Recycling in Surrey, UK

Evaluate demographic and geographic factors in recycling motivation

Survey households (2 urban, 2 rural)

urban study zones:Worcester Park (deprived)Longmead Estates (least deprived)

rural study zones:Middle Burne (deprived)Upper Hale (least deprived)

Case Study:


ArcGIS Network Analyst for road networks

Case Study:


Case Study:


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

Findings

Case Study:Geodemographics & the Financial Service Industry in the UK

Profiling & finding customers Credit scoring Branch location Fuzzy geodemographics

GIS & geodemographics for a competitive edge

Case Study:GD & the Financial Service Industry in the UK

1. Produce a list of account holders of various types (current account, mortgages, savings, etc.)

2. Assign account holder to a census tract by their address

3. 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

Profiling & finding customers

Overlay


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

Credit Scoring

Overlay


Branch Location


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

SolutionDisplay all clusters, esp., clusters similar to dominant cluster


Customer Profiling & Fuzzy Geodemographics


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

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?

Thanks for your patience!

comments or tomatoes welcome

claire m. palmer gis 3130 advanced spatial analysis march 19, 2008 geodemographic analysis

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