Putting the geography into geodemographics: Using multilevel modelling to improve neighbourhood targeting – a case study of Asian pupils in London

Richard Harris () and Yingyu Feng
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Richard Harris: University of Bristol
Yingyu Feng: University of Bristol

Journal of Marketing Analytics, 2016, vol. 4, issue 2, No 4, 93-107

Abstract: Abstract This paper explores the use of multilevel modelling to provide a statistical framework for geodemographic analysis. It argues that combining a neighbourhood classification with a modelling approach allows the levels of the geodemographic hierarchy to be considered simultaneously, identifying those that are most appropriate to the analysis and allowing the apparent differences between neighbourhood types to be considered in regard to their statistical significance, and to the uncertainty of the estimates. The paper shows how the model can be extended to create a cross-classified multiscale model that makes better use of the locational information available to improve the efficiency of the neighbourhood targeting. The ideas are illustrated with a case study using a sample of data and the freely available London Output Area Classification to predict which neighbourhoods in London have the highest percentages of Asian school pupils. The multiscale model is shown to outperform the predictions made using geodemographics alone.

Keywords: geodemographics; multilevel modelling; neighbourhood targeting; London; London output area classification; segmentation (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)

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DOI: 10.1057/s41270-016-0003-1

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