Strategic Analysis of Market Segments Through Self-Organizing ANNs Considering Multiple Attributes

The segmentation of clients in a specific market is very useful to identify different groups of them that let develop specific marketing policies to better suit the demand and to get a higher market share. This item is specially relevant when a new product or service is launched, in order to focus strategies on most relevant clients, reducing costing and increasing the impact of marketing actions. To do that, traditionally the “crisp cluster analysis” technique has been used, but it does not let consider fuzzy and linguistic information characteristic of many strategic variables. To solve this problem, it is proposed a new technique of data treatment based on the “2-tuple” linguistic approach, that will be used to obtain a more realistic global suitability, employed to develop a final Artificial Neural Network (the SOFM model) resuming particular position of market segments in the face of the new product launch.