Communication
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# Geodemographic segmentation

In marketing, 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. [1]

## Acorn (demographics)

Acorn, developed by CACI Limited in London, is a segmentation tool which categorises the United Kingdom’s population into demographic types.

## Australia

Australia, officially the Commonwealth of Australia, is a sovereign country comprising the mainland of the Australian continent, the island of Tasmania and numerous smaller islands.

## Australian Bureau of Statistics

The Australian Bureau of Statistics (ABS) is the independent statistical agency of the Government of Australia.

## Census in Australia

The census in Australia, or officially, the Census of Population and Housing, is a descriptive count of population of Australia on one night, and of their dwellings, generally held quinquennially.

## Census in Canada

A national census in Canada is conducted every five years by Statistics Canada.

## Claritas Prizm

Nielsen PRIZM is a set of geo-demographic segments for the United States, developed by Claritas Inc., which was then acquired by The Nielsen Company.

## Marketing

Marketing is the study and management of exchange relationships.

## Mosaic (geodemography)

Mosaic UK is Experian’s system for classification of UK households.

## Multivariate statistics

Multivariate statistics is a subdivision of statistics encompassing the simultaneous observation and analysis of more than one outcome variable.

## Onomastics

Onomastics or onomatology is the study of the origin, history, and use of proper names.

## Quantity

Quantity is a property that can exist as a multitude or magnitude.

## Self-organizing map

A self-organizing map (SOM) or self-organizing feature map (SOFM) is a type of artificial neural network (ANN) that is trained using unsupervised learning to produce a low-dimensional (typically two-dimensional), discretized representation of the input space of the training samples, called a map, and is therefore a method to do dimensionality reduction.

## References

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