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Acorn (demographics) : ウィキペディア英語版
Acorn (demographics)


Acorn, developed by CACI Limited in London, is a segmentation tool which categorises the United Kingdom’s population into demographic types. It has been built by analysing significant social factors and population behaviour to provide precise information and in-depth understanding of the different types of people and communities across the UK.
Acorn segments households, postcodes and neighbourhoods into 6 categories, 18 groups and 62 types.
== Methodology ==

In March 2013 CACI launched the latest version of Acorn. This took the marketing and demographic industry by surprise largely because the necessary data from the 2011 census was not available for the whole of the UK.
The current version of Acorn has been created using a unique and radically different approach to geodemographics. It does not rely on census data,〔(Taking leave of the Census )〕 but takes advantage of the new data environment created by government policies on Open data and the availability of a number of brand new private sector datasets.
Peter Sleight, Chair of Association of Census Distributors said "The new Acorn has revolutionised geodemographics".
At The Census & Geodemographics Group’s〔(The Census and Geodemographics Group )〕 decennial conference, Tracking a Decade of Changing Britain,〔(Tracking a Decade of Changing Britain )〕 CACI presented a paper on why they had chosen to eschew Census data and how they had gone about developing a new way of creating a demographic segmentation.
Traditionally (since the 1970s), all geodemographic segmentations and classifications were built in broadly the same way.〔(OAC Methodology )〕 A good example of this is the Output Area Classification (OAC). The first OAC was developed in 2005 by the University of Leeds in cooperation with the UK Office for National Statistics' (ONS). It is a free and open geodemographic segmentation based on the 2001 UK Census. Currently, at University College London, the OAC is being rebuilt using the 2011 UK Census.
In the traditional approach census and lifestyle data is fed through statistical software to perform a multi-variate segmentation. The resulting segmentation is analysed, named and described.
The most significant aspect of this ‘’traditional’’ approach is that:
# The same statistical process builds the definition of how to describe communities and allocates local areas (postcode or household) to these types.
# Every local area is classified using the same data variables.
# Every local area is classified using the same statistical algorithm.
The problem with this approach is that housing built after the census cannot be classified primarily because of the requirement to always use the same data and the same algorithm and so, by definition, census data does not and cannot be applied to newly built housing. Furthermore, lifestyle data does not apply either as it takes time to build up a pool of information from new residents. Similarly, data gleaned from things like credit applications can be highly inaccurate if the new housing is a redevelopment of previous housing, since the bulk of information in these traditional data sources can apply to residents of housing that has been demolished.
Having developed a brand new statistical technique to classify such housing, CACI took the decision to throw off the shackles imposed by the traditional approach and develop new approaches for postcodes in other circumstances.
This new approach starts by separating the process of defining the types that describe the population from the process of assigning postcodes to the types. This allows the process of assignment to be done using many different algorithms.
The general principle is to use appropriate data and specific algorithms to give the best segmentation. Examples include; age limited housing, newly built social and private housing, manual allocations, student accommodation, etc.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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