Modern Analysis of Customer Surveys: with applications using R
Customer survey studies deal with customer, consumer and user satisfaction from a product or service. In practice, many of the customer surveys conducted by business and industry are analyzed in a very simple way, without using models or statistical methods. Typical reports include descriptive statistics and basic graphical displays. This book demonstrates how integrating such basic analysis with more advanced tools, provides insights into non-obvious patterns and important relationships between the survey variables. This knowledge can significantly affect the conclusions derived from a survey.
Key features:
* Provides an integrated case studies-based approach to analysing customer survey data.
* Presents a general introduction to customer surveys, within an organization’s business cycle.
* Contains classical techniques with modern and non standard tools.
* Focuses on probabilistic techniques from the area of statistics/data analysis and covers all major recent developments.
* Accompanied by a supporting website containing datasets and R scripts.
Customer survey specialists, quality managers and market researchers will benefit from this book as well as specialists in marketing, data mining and business intelligence fields.
www.wiley.com/go/modern_analysis
STATISTICS IN PRACTICE
A series of practical books outlining the use of statistical techniques in a wide range of applications areas:
* HUMAN AND BIOLOGICAL SCIENCES
* EARTH AND ENVIRONMENTAL SCIENCES
* INDUSTRY, COMMERCE AND FINANCE
Tabela de Conteúdo
Part I: Basic Aspects of Customer Satisfaction Surveys Data Analysis
Chapter 1. Standards and Classical techniques in Data Analysis of Customer Satisfaction Surveys (Kenett, Salini)
Chapter 2. The ABC Annual Customer Satisfaction Survey (Kenett, Salini)
Chapter 3. Sampling, Surveys and Census (Nicolini, Dallavalle)
Chapter 4. Measurement Scales (Bonanomi, Cantaluppi)
Chapter 5. Integrated Analysis (Biffignandi)
Chapter 6. Web Surveys (Furlan, Martone)
Chapter 7. The Concept and Assessment of Customer Satisfaction (Ograjensek, Gal)
Chapter 8. Missing Data and Imputation Methods (Mattei, Mealli, Rubin)
Chapter 9. Outliers and Robustness for Ordinal Data (Riani, Zani)
Part II: Modern Techniques in Customer Satisfaction Surveys Data Analysis
Chapter 10. Causality Models (Mealli, Pacini, Rubin)
Chapter 11. Bayesian Networks (Kenett, Perucca, Salini)
Chapter 12. Log Linear Models (Fienberg, Manrique)
Chapter 13. CUB Models (Iannario, Piccolo)
Chapter 14. The Rasch model (De Battisti, Nicolini, Salini)
Chapter 15. Tree-based Methods and Decision Trees (Galimberti, Sofritti)
Chapter 16. PLS Models (Boari, Cantaluppi)
Chapter 17. Non Linear PCA (Ferrari, Barbero)
Chapter 18. Multidimensional Scaling (Solaro)
Chapter 19. Multilevel Models for Ordinal Data (Grilli, Rampichini)
Chapter 20. Quality Standards and Control Charts Applied to Customer Surveys (Kenett, Deldossi, Zappa)
Chapter 21. Fuzzy Methods and Satisfaction Indices (Zani, Milioli, Morlini)
Appendix: An introduction to R (Iacus)
Sobre o autor
Edited by
RON S. KENETT, KPA Ltd., Raanana, Israel, University of Turin, Italy, and NYU-Poly, Center for Risk Engineering, New York, USA
SILVIA SALINI, Department of Economics, Business and Statistics, University of Milan, Italy
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