Authors:
Catarina Maçãs
;
Evgheni Polisciuc
and
Penousal Machado
Affiliation:
CISUC, Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal
Keyword(s):
Data Glyph, SOM, Visualisation, Force-directed Graph, Customer Profiling, Mixed Data.
Abstract:
With the possibility of storing customer data, retail companies can improve their marketing strategies, creating promotions and special offers specific for individual customers. The application of information visualisation combined with machine learning methods can facilitate the tasks related to customer profiling, and therefore, the creation of individualised campaigns. More specifically, we argue that clustering and segmentation methods, in particular SOM algorithms, foster customer characterisation by defining a shopping topology that can distinguish different patterns of consumption. Furthermore, we believe that adding visual descriptors of the shopping behaviours through the means of data glyphs, can further improve the efficiency and efficacy of SOMs. We present a visualisation method that combines SOMs and data glyphs, with an ultimate goal to reveal purchasing patterns of individual customers. Additionally, we apply two SOM projections: the traditional matrix projection, and
a novel force-directed projection, for a more detailed view over the clusters of the SOM.
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