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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
Autorentext
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
Zusammenfassung
Customer survey studies deals with customers, consumers 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. As demonstrated in this book, integrating such basic analysis with more advanced tools, provides insights on 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.
Inhalt
Foreword xvii
Preface xix
Contributors xxiii
PART I BASIC ASPECTS OF CUSTOMER SATISFACTION
SURVEY DATA ANALYSIS
**1 Standards and classical techniques in data analysis of customer satisfaction surveys 3
Silvia Salini and Ron S. Kenett
1.1 Literature on customer satisfaction surveys 4
1.2 Customer satisfaction surveys and the business cycle 4
1.3 Standards used in the analysis of survey data 7
1.4 Measures and models of customer satisfaction 12
1.4.1 The conceptual construct 12
1.4.2 The measurement process 13
1.5 Organization of the book 15
1.6 Summary 17
References 17
**2 The ABC annual customer satisfaction survey 19
Ron S. Kenett and Silvia Salini
2.1 The ABC company 19
2.2 ABC 2010 ACSS: Demographics of respondents 20
2.3 ABC 2010 ACSS: Overall satisfaction 22
2.4 ABC 2010 ACSS: Analysis of topics 24
2.5 ABC 2010 ACSS: Strengths and weaknesses and decision drivers 27
2.6 Summary 28
References 28
Appendix 29
**3 Census and sample surveys 37
Giovanna Nicolini and Luciana Dalla Valle
3.1 Introduction 37
3.2 Types of surveys 39
3.2.1 Census and sample surveys 39
3.2.2 Sampling design 40
3.2.3 Managing a survey 40
3.2.4 Frequency of surveys 41
3.3 Non-sampling errors 41
3.3.1 Measurement error 42
3.3.2 Coverage error 42
3.3.3 Unit non-response and non-self-selection errors 43
3.3.4 Item non-response and non-self-selection error 44
3.4 Data collection methods 44
3.5 Methods to correct non-sampling errors 46
3.5.1 Methods to correct unit non-response errors 46
3.5.2 Methods to correct item non-response 49
3.6 Summary 51
References 52
**4 Measurement scales 55
Andrea Bonanomi and Gabriele Cantaluppi
4.1 Scale construction 55
4.1.1 Nominal scale 56
4.1.2 Ordinal scale 57
4.1.3 Interval scale 58
4.1.4 Ratio scale 59
4.2 Scale transformations 60
4.2.1 Scale transformations referred to single items 61
4.2.2 Scale transformations to obtain scores on a unique interval scale 66
Acknowledgements 69
References 69
**5 Integrated analysis 71
Silvia Biffignandi
5.1 Introduction 71
5.2 Information sources and related problems 73
5.2.1 Types of data sources 73
5.2.2 Advantages of using secondary source data 73
5.2.3 Problems with secondary source data 74
5.2.4 Internal sources of secondary information 75
5.3 Root cause analysis 78
5.3.1 General concepts 78
5.3.2 Methods and tools in RCA 81
5.3.3 Root cause analysis and customer satisfaction 85
5.4 Summary 87
Acknowledgement 87
References 87
**6 Web surveys 89
Roberto Furlan and Diego Martone
6.1 Introduction 89
6.2 Main types of web surveys 90
6.3 Economic benefits of web survey research 91
6.3.1 Fixed and variable costs 92
6.4 Non-economic benefits of web survey research 94
6.5 Main drawbacks of web survey research 96
6.6 Web surveys for customer and employee satisfaction projects 100
6.7 Summary 102
References 102
**7 The concept and assessment of customer satisfaction 107
Irena Ograjensek and Iddo Gal
7.1 Introduction 107
7.2 The qualitysatisfactionloyalty chain 108
7.2.1 Rationale 108
7.2.2 Definitions of customer satisfaction 108 &...