By means of a case study concerned with Italian espresso coffee, this contribution shows how a structured combination of statistical techniques in the mainframe of sensory analysis permits to attain interesting results, concerned with consumers’ sensory satisfaction. The body of the analysis is represented by the implementation of the CUB models in order to quantify the perceptions about the product. The obtained sensory satisfaction indices can be immediately used, for example for product development in marketing management. In addition, they can be the starting point for further quantitative analyses, according to the recorded information about the product, if available. In this contribution, we use the algorithmic variable importance measurement allowed by the Random Forest approach in order to recover useful information for marketing decisions about advertising.
A statistical analysis on sensory data: the Italian espresso case study
MANISERA, Marica;ZUCCOLOTTO, Paola
2013-01-01
Abstract
By means of a case study concerned with Italian espresso coffee, this contribution shows how a structured combination of statistical techniques in the mainframe of sensory analysis permits to attain interesting results, concerned with consumers’ sensory satisfaction. The body of the analysis is represented by the implementation of the CUB models in order to quantify the perceptions about the product. The obtained sensory satisfaction indices can be immediately used, for example for product development in marketing management. In addition, they can be the starting point for further quantitative analyses, according to the recorded information about the product, if available. In this contribution, we use the algorithmic variable importance measurement allowed by the Random Forest approach in order to recover useful information for marketing decisions about advertising.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
