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Acorn (demographics)

From Wikipedia, the free encyclopedia

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.

The Acorn structure


In March 2014 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,[1] 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[2] decennial conference, Tracking a Decade of Changing Britain,[3] 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.[4] 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.

 Traditional methodology
Traditional methodology

The most significant aspect of this ‘’traditional’’ approach is that:

  1. The same statistical process builds the definition of how to describe communities and allocates local areas (postcode or household) to these types.
  2. Every local area is classified using the same data variables.
  3. 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.

 Acorn’s methodology
Acorn’s methodology

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.

New Data Environment

This new approach is better suited to the new data environment as increasingly more local information is being published as Open Data and more local information is available from commercial sources. The first benefit of the new approach is that any future data that becomes available can be incorporated into the segmentation process, thereby bringing about improved updating and effectively ‘future-proofs’ the solution. In Acorn terms, it is the equivalent of having a new census every year. The second benefit is that it is not essential to have data for all of the United Kingdom. If the Acorn solution can be improved for only part of the country without losing anything elsewhere, then it is clearly advantageous to do so. With devolved government, a great deal of Open Data is released covering only England, only Scotland, only Wales etc. The traditional approach could not use this data since it required the same data for every postcode. The new approach allows this data to be used effectively.

External links


This page was last modified on 12 March 2017, at 22:54.
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