Despite the inclusion of some non-Census variables, the traditional proprietary geodemographic classification systems remain purely demand based and static. Nevertheless it has been shown that geodemographics can be extended using supply-side and change variables to create a classification system that measures small areas on the characteristics of the labour market and their propensity to change over time, in addition to the likely levels of affluence more commonly found in such systems. \ud This paper presents a number of methods that will later be used to evaluate the success of adding these supply-side and change variables. A static demand classification is created in the style of traditional geodemographic system. Various techniques are then used to evaluate the robustness of the classification and to identify the most important cluster formative variables. Furthermore, this classification is benchmarked against an existing geodemographic system, Experían Ltd's GB MOSAIC system. It is hoped that this will show that the demand variables used here provide a suitable base to operationalise the theories behind extending geodemographics. In order to show how the evaluation techniques can be used to monitor the success of adding different supply-side and dynamic datasets, a suite of property transaction variables are added to the classification. The effect of these variables upon the robustness of the taxonomy and the importance of the individual variables is then displayed. \u
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