Rosa Arboretti received her PhD in Statistical Methodology for Scientific Research at the University of Bologna. She is currently Associate Professor at the Department of Civil, Architectural and Environmental Engineering of the University of Padova. Her main research interests are related to Statistical Methods applied to Biomedicine and Engineering.

Arne Bathke is Full Professor of Statistics at the University of Salzburg. His main research interests are related to Nonparametric and Multivariate Statistics applied in different fields from Social Sciences to Biomedicine and Engineering.

Stefano Bonnini is Associate Professor of Statistics at the Department of Economics and Management of the University of Ferrara. His main research interests are related to Nonparametric Statistics and Statistics applied to Economic and Social Sciences, Health Sciences and Engineering.

Paolo Bordignon is a Psychologist graduated at the University of Padova. He received his PhD at the Department of Management and Engineering of the University of Padova. His main research interests are related to Choice and Latent Statistical Models for Marketing Research.

Eleonora Carrozzo is a Post-Doc Research Fellow at the Department of Management and Engineering of the University of Padova where she received her PhD. Her main interests are related to Non-parametric Sstatistical Methods for Multivariate Hypothesis Testing and Ranking with application in Engineering and Biostatistics.

Livio Corain is Assistant Professor at the Department of Management and Engineering of the University of Padova. His main research interests are related to Nonparametric Methods for Ranking and Multivariate Hypothesis Testing, Quality Control and Applied Statistics for Engineering and Biomedical studies.

Luigi Salmaso is Full Professor of Statistics at the Department of Management and Engineering of the University of Padova. His main research interests include Biostatistics, Statistical Methods for Marketing Research, Design of Experiments, Nonparametric Statistics and Industrial Statistics.

Chapter 1. The CUB models.- Chapter 2. Customer satisfaction heterogeneity.- Chapter 3. Ranking multivariate populations.- Chapter 4. Composite indicators and satisfaction profiles.- Chapter 5. Analyzing Survey Data Using Multivariate Rank-Based Inference

This book deals with problems related to the evaluation of customer satisfaction in very different contexts and ways. Often satisfaction about a product or service is investigated through suitable surveys which try to capture the satisfaction about several partial aspects which characterize the perceived quality of that product or service. This book presents a series of statistical techniques adopted to analyze data from real situations where customer satisfaction surveys were performed.

The aim is to give a simple guide of the variety of analysis that can be performed when analyzing data from sample surveys: starting from latent variable models to heterogeneity in satisfaction and also introducing some testing methods for comparing different customers. The book also discusses the construction of composite indicators including different benchmarks of satisfaction. Finally, some rank-based procedures for analyzing survey data are also shown.