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Chapter 48: Latent Segments Analysis
Latent segments analysis (LSA) has emerged as a segmentation/clustering probability model based tool: it relies on the estimation of a finite mixture model. The general aim of LSA is to identify the latent segments required to explain the associations among a set of observed variables (the segmentation base variables) and to allocate observations to these segments.
There are several applications of LSA illustrating its use in segmentation. As an example, one can consider segmenting commercial bank customers, consumer segmentation on the basis of product usage or segmentation of customers on the basis of benefits.
The LSA approach to segmentation offers some advantages when compared with other techniques. For example, it provides a means of selecting the number of segments and is able ...