R for Marketing Research and Analytics

Welcome to R.- The R Language.- Describing Data.- Relationships Between Continuous Variables.- Comparing Groups: Tables and Visualizations.- Comparing Groups: Statistical Tests.- Identifying Drivers of Outcomes: Linear Models.- Reducing Data Complexity.- Additional Linear Modeling Topics.- Confirmatory Factor Analysis and Structural Equation Modeling.- Segmentation: Clustering and Classification.- Association Rules for Market Basket Analysis.- Choice Modeling.- Conclusion.- Appendix: R Versions and Related Software.- Appendix: Scaling up.- Appendix: Packages Used.- Index.

Chris Chapman is a Senior Quantitative Researcher at Google. He is also a member of the editorial board of Marketing Insights magazine and the Marketing Insights Council of the American Marketing Association, and has served as chair of the AMA Advanced Research Techniques Forum and AMA Analytics with Purpose conferences. He is an enthusiastic contributor to the quantitative marketing community, where he regularly presents innovations in strategic research and teaches workshops on R and analytic methods.

"R for Marketing Research and Analytics is the perfect book for those interested in driving success for their business and for students looking to get an introduction to R. While many books take a purely academic approach, Chapman (Google) and Feit (Formerly of GM and the Modellers) know exactly what is needed for practical marketing problem solving. I am an expert R user, yet had never thought about a textbook that provides the soup-to-nuts way that Chapman and Feit: show how to load a data set, explore it using visualization techniques, analyze it using statistical models, and then demonstrate the business implications. It is a book that I wish I had written." -- Eric Bradlow, K.P. Chao Professor, Chairperson, Wharton Marketing Department and Co-Director, Wharton Customer Analytics Initiative

"R for Marketing Research and Analytics provides an excellent introduction to the R statistical package for marketing researchers.  This is a must-have book for anyone who seriously pursues analytics in the field of marketing.  R is the software gold-standard in the research industry, and this book provides an introduction to R and shows how to run the analysis.  Topics range from graphics and exploratory methods to confirmatory methods including structural equation modeling, all illustrated with data.  A great contribution to the field!" -- Greg Allenby, Helen C. Kurtz Chair in Marketing, Professor of Marketing and Professor of Statistics, Ohio State University

"Chris Chapman's and Elea Feit's engaging and authoritative book nicely fills a gap in the literature.  At last we have an accessible book that presents core marketing research methods using the tools and vernacular of modern data science.  The book will enable marketing researchers to up their game by adopting the R statistical computing environment.  And data scientists with an interest in marketing problems now have a reference that speaks to them in their language."   

James Guszcza, Chief Data Scientist,

"The monograph presents various numerous illustrations for R language, with setting the data, applying R codes, and interpreting the results obtained. It is written in a very friendly attitude to readers, giving an immediate practical guide to solving real marketing research problems." (Stan Lipovetsky, Technometrics, Vol. 58 (3), August, 2016)

"R for Marketing Research and Analytics is a clearly written, well-organized, comprehensive, and readable guide to using R ... for marketing research and analytics. ... For many readers-even for those who know R and have marketing research and analytics experience-this book can be a valuable resource. ... used as a reference by marketing researchers and analysts, by engineering and business practitioners who wish to learn more about the analyses of customer and marketing data ... ." (R. Jean Ruth, Interfaces, Vol. 46 (3), May-June, 2016)

"The authors take care to guide the reader through the difficult task of data analysis of marketing data with R. ... It is well written, in a colloquial and friendly tone. The reader often has the feeling that the authors talk directly to her. ... I find the book to be a very welcome addition to the Use R! series and the marketing research and business analytics world. I can wholeheartedly recommend it ... ." (Thomas Rusch, Journal of Statistical Software, Vol. 67 (2), October, 2015)