Cluster Analysis in Marketing Research

Thomas Reutterer () and Daniel Dan ()
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Thomas Reutterer: WU Vienna University of Economics and Business
Daniel Dan: Modul University Vienna

A chapter in Handbook of Market Research, 2022, pp 221-249 from Springer

Abstract: Abstract Cluster analysis is an exploratory tool for compressing data into a smaller number of groups or representing points. The latter aims at sufficiently summarizing the underlying data structure and as such can serve the analyst for further consideration instead of dealing with the complete data set. Because of this data compression property, cluster analysis remains to be an essential part of the marketing analyst’s toolbox in today’s data rich business environment. This chapter gives an overview of the various approaches and methods for cluster analysis and links them with the most relevant marketing research contexts. We also provide pointers to the specific packages and functions for performing cluster analysis using the R ecosystem for statistical computing. A substantial part of this chapter is devoted to the illustration of applying different clustering procedures to a reference data set of shopping basket data. We briefly outline the general approach of the considered techniques, provide a walk-through for the corresponding R code required to perform the analyses, and offer some interpretation of the results.

Keywords: Cluster analysis; Hierarchical clustering; k-centroid clustering; k-medoid clustering; Marketing analysis; Marketing research (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-57413-4_11

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DOI: 10.1007/978-3-319-57413-4_11

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