Applied Marketing Analytics Using R

Marketing has become increasingly data-driven in recent years as a result of new emerging technologies such as AI, granular data availability and ever-growing analytics tools. With this trend only set to continue, it’s vital for marketers today to be comfortable in their use of data and quantitative approaches and have a thorough grounding in understanding and using marketing analytics in order to gain insights, support strategic decision-making, solve marketing problems, maximise value and achieve success. Taking a very hands-on approach with the use of real-world datasets, case studies and R (a free statistical package), this book supports students and practitioners to explore a range of marketing phenomena using various applied analytics tools, with a balanced mix of technical coverage alongside marketing theory and frameworks. Chapters include learning objectives, figures, tables and questions to help facilitate learning. Also included online with the datasets are software codes and solutions (R Markdowns, HTML files) to use with the book, as well as PowerPoint slides, a teaching guide and a testbank for instructors teaching a marketing analytics course. This book is essential reading for advanced level marketing students and marketing practitioners who want to become cutting-edge marketers. Dr. Gokhan Yildirim is an Associate Professor of Marketing at Imperial College Business School, London. Dr. Raoul V. Kübler is an Associate Professor of Marketing at ESSEC Business School, Paris.

This book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical models from a conceptual point of view with a minimal amount of mathematics, presuming only an introductory knowledge of statistics. Hands-on chapters accelerate the learning curve by asking readers to interact with R from the beginning. Core topics include the R language, basic statistics, linear modeling, and data visualization, which is presented throughout as an integral part of analysis. Later chapters cover more advanced topics yet are intended to be approachable for all analysts. These sections examine logistic regression, customer segmentation, hierarchical linear modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a minimally complex approach, demonstrating and explaining Bayesian methods alongside traditional analyses for analysis of variance, linear models, and metric and choice-based conjoint analysis. With its emphasis on data visualization, model assessment, and development of statistical intuition, this book provides guidance for any analyst looking to develop or improve skills in R for marketing applications.

Marketing analytics is important to today's business organizations as it lets them measure performance of their marketing resources and channels and in turn plays a vital role in making business strategies and decisions. The present book, following application-based approach, helps readers to understand the usage of analytics in different marketing contexts such as identifying customer preferences, customer-segmentation, pricing, forecasting, advertising, competitive analysis, perceptual mapping, etc. using SPSS software (Modeler, Statistics and AMOS Graphics). Practical applications in each chapter, with supported screenshots, guide readers to apply different analytical techniques in marketing as they learn. This book is an indispensable companion for the postgraduate students of management with specialization in marketing. Also, the book will prove valuable for the Management Development Programs, Data Analysts, and Researchers in the field. It enables them to identify marketing problems, carry out research efficiently, process the data in a simple way using SPSS, and create reports in a systematic manner. TARGET AUDIENCE • MBA (Marketing) • Data Analysts • Management Development Programme

Following an application-based approach, this book helps readers to understand the usage of analytics in different marketing contexts, such as identifying customer preferences, customer-segmentation, pricing, forecasting, advertising, competitive analysis, perceptual mapping, using SPSS software (Modeler, Statistics and AMOS Graphics).

Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems. It also gives insight into some of the challenges faced when deploying these tools. Extensively classroom-tested, the tex

The 2nd edition of R for Marketing Research and Analytics continues to be the best place to learn R for marketing research. This book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical models from a conceptual point of view with a minimal amount of mathematics, presuming only an introductory knowledge of statistics. Hands-on chapters accelerate the learning curve by asking readers to interact with R from the beginning. Core topics include the R language, basic statistics, linear modeling, and data visualization, which is presented throughout as an integral part of analysis. Later chapters cover more advanced topics yet are intended to be approachable for all analysts. These sections examine logistic regression, customer segmentation, hierarchical linear modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a minimally complex approach, demonstrating and explaining Bayesian methods alongside traditional analyses for analysis of variance, linear models, and metric and choice-based conjoint analysis. With its emphasis on data visualization, model assessment, and development of statistical intuition, this book provides guidance for any analyst looking to develop or improve skills in R for marketing applications. The 2nd edition increases the book’s utility for students and instructors with the inclusion of exercises and classroom slides. At the same time, it retains all of the features that make it a vital resource for practitioners: non-mathematical exposition, examples modeled on real world marketing problems, intuitive guidance on research methods, and immediately applicable code.

Tomorrow's professionals need a practical, customer-centric understanding of marketing's role in business and critical thinking skills to help their organizations succeed. Applied Marketing, 1st Canadian Edition helps students learn practical, modern marketing concepts appropriate for the principles of marketing course by applying them to the latest business scenarios of relatable brands like This Bar Saves Lives and GoPro. This comprehensive yet concise text is co-authored by Professors Rochelle Grayson and Daniel Padgett and practitioner Andrew Loos, and blends current academic theory with an agency-owner perspective to help students get an insider's look at how top businesses operate. With many Canadian specific examples created specifically for this course, students can relate concepts learned in the classroom to marketing topics and events taking place in their backyard.

Marketing Analytics provides guidelines in the application of statistics using IBM SPSS Statistics Software (SPSS) for students and professionals using quantitative methods in marketing and consumer behavior. With simple language and a practical, screenshot-led approach, the book presents 11 multivariate techniques and the steps required to perform analysis. Each chapter contains a brief description of the technique, followed by the possible marketing research applications. One of these applications is then used in detail to illustrate its applicability in a research context, including the needed SPSS commands and illustrations. Each chapter also includes practical exercises that require the readers to perform the technique and interpret the results, equipping students with the necessary skills to apply statistics by means of SPSS in marketing and consumer research. Finally, there is a list of articles employing the technique that can be used for further reading. This textbook provides introductory material for advanced undergraduate and postgraduate students studying marketing and consumer analytics, teaching methods along with practical software-applied training using SPSS. Support material includes two real data sets to illustrate the techniques’ applications and PowerPoint slides providing a step-by-step guide to the analysis and commented outcomes. Professionals are invited to use the book to select and use the appropriate analytics for their specific context.