Lecture 10 - Geodemographics Flashcards
Geodemographics
Geo - geography / place
Demo - people
Graphics - Writing / analyising / research
What is geodemography?
- Science of profiling / analysing people based on where they live
- You are where you live (birds of a feather flock together)
- Where you are says something about who you are
2 principles of geodemography
- people living in areas close to each other will have more in common, people farther away will have more differences
- you can also group people based on their characteristics no matter where they live (example: students)
Charles Booth
- 1889
- looked at how people in London cluster based on income, # family members, employment, etc
- used this information to map where different classes clustered
Concentric Zone Theory
- 1925
- Explain urban social structures with concentric rings
- CBD in the middle, then factory zone, transition zone, working class zone, residential zone, commuter zone
-each zone is a geographical area distinguished by both physical individuality and by social, economic, and cultural characteristics of population
Commercial examples
CACA, Claritas, Experian
- classify people based on where they live, analyse and sell results to companies, governments, etc.
- help decide where to build a shop or business, etc
- geodemographic segmentation assumes that consumer behaviour can be predicted by ‘who you are & where you live’
Geodemographic segmentation example (PersonicX)
profile market segments
- profile your customer base (behavior, demographic, lifestyle)
- identify market segments
- track performance of products or customer segments
- recognise customer risks
- target market spending to get returns on advertisement investing
- analyze campaign performance
- expand business with existing customers
- explore customer insights through third party data
Geodemographic classification (PersonicX)
-classify groups and sub-clusters
-group / cluster example:
group = big ethnic families
cluster B05 = young renting families
cluster B07 = kids & comfort
-profile example:
includes house income, education, driving, spending, percent of the population, defining features, etc
Geodemographic cluster scale (PersonicX)
- NZ’s smallest scale for census is the meshblock
- PersonicX gathers more detailed information for households/properties within each meshblock
How to create geodemographics (6)
- gather data (from census or with surveys)
- area level variables
- evaluate input variables (go there to see if data representative of real world)
- cluster ‘socially similar’ neighbourhoods together
- optimisation process & manual intervention
- form a class hierarchy & label
Gather data
- often census is the sole data source
- in data-rich countries census supplemented by property registers, electoral registers, car registration, etc
- non-census data is useful, gets info from more privileged people, available at finer aggregation, can fill gaps between censuses
- link into a single level of geography
Create area level variables
- more variables from different sources = more meaningful clusters
- relate ‘count’ variables to ‘base’ count to get rates (total cars divided by adult population)
- group counts:
- # of residents in different age groups
- employment by industry
Evaluate input variables
- is the variable skewed (not a normal bell curve)
- some variables may not be deemed appropriate for use in clustering
Cluster ‘socially similar’ neighborhoods together
- depends on cluster method
- 2 types: hierarchical and non-hierarchical (k-means)
Hierarchical
each neighborhood forms a separate cluster, then each cluster merges sequentially on similarity, reducing # of clusters in each step until 1 cluster left
