Modern Analysis of Customer Surveys
With Applications Using R
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This book introduces customer satisfaction surveys, with a focus on the classical problems of analyzing them. Each chapter describes, in detail, a different technique applied to the standard dataset along with R scripts on a supporting website. Most of the techniques featured are applied to a standard set of data collected from 266 companies (customers) participating in the ABC Annual Customer Satisfaction Survey conducted by KPA in 2004 for an international electronics company. The data refers to a questionnaire that covered a wide range of service and product perspectives.
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.
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.
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.
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