Further Considerations on Latent Segmentation Techniques for Customer Heterogeneity Detection

Gabriele Cantaluppi, Giuseppe Boari

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Latent segmentation procedures are usually aimed at detecting the heterogeneity of statisitical units with reference to a system of relationships described by a structural equation model with latent variables (SEM-LV). After a short review of hte main proposals given in the literature, we present a descriptive two-step procedure, wich first considers either an a-priori or a post-hoc segmentation approach: the former is based upon the existence of proper classification variables; the latter defines as classificaiton variables the latent scores estimated by a global SEM-LV model. In the second step a cluster analysis is performed by using the previously defined grouping vairables, in order to improve the classification by means of a cluster-wise Partial Least Squares algorithm; the classification refinement is executed with reference both to the SEM inner and outer models.
Original languageEnglish
Title of host publicationClassification and Data Analysis 2009, Book of Short Papers, 7° Meeting of the Classification and Data Analysis Group of the Italian Statistical Society
Pages255-258
Number of pages4
Publication statusPublished - 2009
EventClassification and Data Analysis 2009, 7° Meeting of the Classification and Data Analysis Group of the Italian Statistical Society - Catania
Duration: 9 Sep 200911 Sep 2009

Conference

ConferenceClassification and Data Analysis 2009, 7° Meeting of the Classification and Data Analysis Group of the Italian Statistical Society
CityCatania
Period9/9/0911/9/09

Keywords

  • Customer Heterogeneity Detection
  • Latent Segmentation

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