east massachusetts geodemographic classification
DESCRIPTION
The presentation outlines the process of East Massachusetts Geodemographic Classification design following methodology developed by Dr.Dan Vickers (University of Sheffield).TRANSCRIPT
EAST MASSACHUSETTS GEODEMOGRAPHIC CLASSIFICATION
Stas Sushkov
Maria Sushkova
Introduction
Geodemographics is the analysis of people by where they live (Sleight, 1996)
Geodemographic classification categories neighborhoods based on their socio-economic and lifestyle characteristics.
Geodemographic segmentation is a multivariate statistical classification technique for discovering whether the individuals of a population fall into different groups by making quantitative comparisons of multiple characteristics with the assumption that the differences within any group should be less than the differences between groups. (Wikipedia)
Introduction
Market Research• Survey analysis• Concept testing• Product positioning • New product information• Image and awareness
Market Analysis• Site Selection• Market share analysis• Trade area analysis• New product rollout• Market entry planning• Test marketing
Advertising Media• Media analysis• Ad/Product positioning• Creative development• Media scheduling• Ad budget allocation• Advertising sales
Direct Marketing• Mailing list selection• Freestanding inserts• Response analysis• Program evaluation
Geodemographic classification applications
Source: adapted from Harris et al. 2005
Research Objectives
To build the geodemographic classification of East Massachusetts based on results of 2000 US Census
To create the multipurpose basis for further research analysis
To develop and test methodology for more comprehensive geodemographic classifications to be elaborated
Research Methodologies
The methodology applied for creation of East Massachusetts classification was developed by Dr. Dan Vickers (University of Sheffield) and described in his work “Multi-level Integrated
Classification Based on the 2001 Census”. Dr. Vickers has created The National Classification of Census Output Areas for UK, this classification was officially endorsed by the Office for National Statistics (UK). http://www.sasi.group.shef.ac.uk/area_classification/index.html
Clustering Process
Selection of cluster objects (operational
taxonomic units) Variables selection
Variables standardisation
Clustering method selection
Identification of cluster number
Interpretation, testing and mapping
of clusters
Classification Inputs
The 4,340 block groups of 9 Massachusetts counties were used: Essex, Middlesex, Suffolk, Norfolk, Bristol, Plymouth, Barnstable, Worchester
Total number of households: 2,117,000
Overall population: 5,510,000
Project Results
Various approaches to the classification design were evaluated and more appropriate ones were selected
The geodemographic classification was visually represented and tested in ArcGis, Google Earth and Maptube
5 super clusters were identified, narratively described and mapped.
Geographic database of cluster locations has been created
Mapping Clusters
Mapping clusters in ArcGis using full boundaries – each block group belongs to a certain cluster. Although the population clustering is obvious, uneven census sizes gives wrong perception of the population density. Thus low populated areas dominate on the map
Mapping Clusters
Mapping clusters in Arcgis using block group centroids represents cluster distribution more accurately and corresponds with population density.
Mapping Clusters
Mapping the classification visualizes the geodemographic clusterisation and shows that the population is clustered. For example brown dots are grouped representing one of the cluster areas.
The created clusters can also be exported to Google Earth…
Mapping Clusters
or Maptube.org – the online resource which allows to create public maps for free. East Massachusetts Geodemographic Classification Map can be easily accessed there.
Naming and Describing Clusters
5 clusters of the classification were named:
1. Common City Dwellers
2. City Strugglers
3. Wealthy Suburbs
4. University Students and Downtown Residents
5. Suburban Middle Class
#1 Common City Dwellers
White populationBlack populationAsian population
Workers
Transportation to work; Car
Transportation to work; Transit
Transportation to work; Walk or Bicycle
Working from home
Population with high school degree
Pop with bachelor of higher degree
Medium hh income
Median number of rooms
Owner occupied dwellings
Medium house value
Hh without mortgage
Population paying high mortgage and owner cost
Foreign born population
Hh with Social Security income
Hh with Supplemental Security Income (SSI) and/or public assistance income
Poor population
Medium rentAge 0-9
Age 10-17Age 18-24Age 25-29Age 45-64Age 65+
1 person hh
2 person non family hh
2 person family hh
5+ person family hh
Disabled pop
Urban pop
Work 35+ h per week
Work 1-14 h per week
Unemployed pop
1 parent hh
Hh with 2+ vehicles
Self employed pop
Housing lacking kitch and plumb facilities
Hh with no cars
Own children U18 pop
Unempl male over16 pop
Single pop
Married popPop Employee of Private Comp
Vehicles per 100 residents
-50
0
50
#1 Common City Dwellers
Represented by the “average” middle class population residing mainly in high populated metropolitan areas.
Close to average household income ($48,000*; mean - $55,600) and educational level (20% with bachelor or higher degree). House value is around $185,000 which is 13% lower than the mean.
High percentage (49%) of Common City Dwellers rent their primary residence, in comparison with 38% mean.
Within this cluster the share of households with 2+ cars is 30% while the mean is 42%.
*Note: Here and further medium household income, medium house value and medium rent are shown based on the values of 2000 year when the US 2000 Census took place.
See this cluster 3D on Google Maps
#2 City Strugglers
White populationBlack populationAsian populationWorkers
Transportation to work; Car
Transportation to work; Transit
Transportation to work; Walk or Bicycle
Working from home
Population with high school degree
Pop with bachelor of higher degree
Medium hh income
Median number of rooms
Owner occupied dwellings
Medium house value
Hh without mortgage
Population paying high mortgage and owner cost
Foreign born population
Hh with Social Security income
Hh with Supplemental Security Income (SSI) and/or public assistance income
Poor populationMedium rent
Age 0-9Age 10-17Age 18-24Age 25-29Age 45-64
Age 65+1 person hh
2 person non family hh
2 person family hh
5+ person family hh
Disabled pop
Urban pop
Work 35+ h per week
Work 1-14 h per week
Unemployed pop
1 parent hh
Hh with 2+ vehicles
Self employed pop
Housing lacking kitch and plumb facilities
Hh with no cars
Own children U18 pop
Unempl male over16 pop
Single popMarried pop
Pop Employee of Private CompVehicles per 100 residents
-50
0
50
#2 City Strugglers Mostly concentrated in areas close to the city center. 26% of this cluster are people for whom “poor” status
is determined. High level of black population, and population born
outside the US. High share of one parent households (41%, mean -
14%). High percentage of households with no cars (33%,
mean -12%), and who travel to work by transit. Almost ¾ of City Strugglers rent their residence.
Median household income – $28,400, which is almost 2 times lower than the average. Median house value – $136,000.
Only 7% of this population have bachelor or higher degree (mean-23%).
See this cluster area 3D on Google Maps
#3 Wealthy Suburbs
White populationBlack populationAsian populationWorkers
Transportation to work; Car
Transportation to work; Transit
Transportation to work; Walk or Bicycle
Working from home
Population with high school degree
Pop with bachelor of higher degree
Medium hh income
Median number of rooms
Owner occupied dwellings
Medium house value
Hh without mortgage
Population paying high mortgage and owner cost
Foreign born population
Hh with Social Security income
Hh with Supplemental Security Income (SSI) and/or public assistance income
Poor populationMedium rent
Age 0-9Age 10-17Age 18-24Age 25-29Age 45-64
Age 65+1 person hh
2 person non family hh
2 person family hh
5+ person family hh
Disabled pop
Urban pop
Work 35+ h per week
Work 1-14 h per week
Unemployed pop
1 parent hh
Hh with 2+ vehicles
Self employed pop
Housing lacking kitch and plumb facilities
Hh with no cars
Own children U18 pop
Unempl male over16 pop
Single popMarried pop
Pop Employee of Private CompVehicles per 100 residents
-50
0
50
#3 Wealthy Suburbs Represented by people with high medium
household income ($82,000; mean - $55,600) and high medium house value ($307,000; mean - $211,000) , who mostly reside in suburban areas.
Low share of black (1%; mean - 6%) and foreign born (8%; mean - 3%) population.
High proportion of households with 2+ cars (64%; mean 49%) and low percentage of households with no cars.
High share of population with bachelor or higher degree (35%; mean - 23%).
Low proportion of one parent households (6%; mean – 14%).
High average rent price - $800 (mean - $680), and higher than average share of population who pays high mortgage and housing costs (8%; mean – 3%).
See this cluster area 3D on Google Maps
#4 University Students and Downtown Residents
White populationBlack populationAsian populationWorkers
Transportation to work; Car
Transportation to work; Transit
Transportation to work; Walk or Bicycle
Working from home
Population with high school degree
Pop with bachelor of higher degree
Medium hh income
Median number of rooms
Owner occupied dwellings
Medium house value
Hh without mortgage
Population paying high mortgage and owner cost
Foreign born population
Hh with Social Security income
Hh with Supplemental Security Income (SSI) and/or public assistance income
Poor populationMedium rent
Age 0-9Age 10-17Age 18-24Age 25-29Age 45-64
Age 65+1 person hh
2 person non family hh
2 person family hh
5+ person family hh
Disabled pop
Urban pop
Work 35+ h per week
Work 1-14 h per week
Unemployed pop
1 parent hh
Hh with 2+ vehicles
Self employed pop
Housing lacking kitch and plumb facilities
Hh with no cars
Own children U18 pop
Unempl male over16 pop
Single popMarried pop
Pop Employee of Private CompVehicles per 100 residents
-50
0
50
#4 Downtown Residents and University Students
This cluster members mostly resides in vicinity to universities, or in downtown of metropolitan cities.
Extremely high proportion of people do not use a car as a means of transportation to get to work (64%; mean - 29%), instead they take public transit (29%; mean - 10%), use a bicycle or walk (23%; mean - 5%). Low share of households with 2+ cars (12%; mean – 42%).
High percentage of population with bachelor or higher degree (41%; mean 23%). Medium income ($49,000; mean – $55,600), medium house value ($276,000; mean – $211,000).
High average rent - $910 (mean - $680) and low proportion of residence owners (28%; mean 61%).
See this cluster area 3D on Google Maps
#5 Suburban Middle Class
White populationBlack populationAsian population
WorkersTransportation to work; Car
Transportation to work; Transit
Transportation to work; Walk or Bicycle
Working from home
Population with high school degree
Pop with bachelor of higher degree
Medium hh income
Median number of rooms
Owner occupied dwellings
Medium house value
Hh without mortgage
Population paying high mortgage and owner cost
Foreign born population
Hh with Social Security income
Hh with Supplemental Security Income (SSI) and/or public assistance income
Poor population
Medium rentAge 0-9
Age 10-17Age 18-24Age 25-29Age 45-64Age 65+
1 person hh
2 person non family hh
2 person family hh
5+ person family hh
Disabled pop
Urban pop
Work 35+ h per week
Work 1-14 h per week
Unemployed pop
1 parent hh
Hh with 2+ vehicles
Self employed pop
Housing lacking kitch and plumb facilities
Hh with no cars
Own children U18 pop
Unempl male over16 pop
Single popMarried pop
Pop Employee of Private CompVehicles per 100 residents
-50
0
50
#5 Suburban Middle Class
The cluster which groups middle class households located in suburban areas.
Mostly white population (96%; mean - 83%).
84% (mean - 72%) use car to go to work, 55% (mean- 42%) of households have 2+ cars. Only 5% of households have no car.
Household median income is almost the same as the mean - $56,000, but average house value ($175,000) is lower than the mean ($211,000).
Large proportion of owner occupied households (78%; mean – 62%).
See this cluster area 3D on Google Maps
References Callingham, M. (2005), From areal classification to geodemographics, paper
presented at the Demographic User Group Conference, Royal Society, London 10th November 2005.
Debenham, J. E. (2002), Understanding Geodemographic Classification: Creating The Building Blocks For An Extension, Working Paper 02/1 School of Geography, University of Leeds [online] http://www.geog.leeds.ac.uk/wpapers/02-1.pdf
Harris, R., Sleight, P. and Webber, R. (2005), Geodemographics, GIS and Neighbourhood Targeting, London, Wiley
Longley, P. A. (2005), Geographical Information Systems: a renaissance of geodemographics for public service delivery, Progress in Human Geography, 29(1)
Sleight, P. (2004) Targeting customers: How to Use Geodemographic and Lifestyle Data in Your Business, Henley-on –Thames, World Advertising Research Centre
Vickers, D. (2006) , Multi-level Integrated Classification Based on the 2001 Census, The University of Leeds
Webber, R. and Farr, M. (2001) , MOSAIC-From an area classification system to household classification, Journal of Targeting, Measurement and Analysis for Marketing,10(1).