R for Marketing Research and Analytics

Author: Chris Chapman
Publisher: Springer
ISBN: 9783319144368
Release Date: 2015-03-09
Genre: Business & Economics

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.

R for Marketing Research and Analytics

Author: Christopher N. Chapman
Publisher: Springer
ISBN: 3319144359
Release Date: 2015-03-25
Genre: Business & Economics

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 Data Science

Author: Thomas W. Miller
Publisher: FT Press
ISBN: 9780133887341
Release Date: 2015-05-02
Genre: Business & Economics

Now , a leader of Northwestern University's prestigious analytics program presents a fully-integrated treatment of both the business and academic elements of marketing applications in predictive analytics. Writing for both managers and students, Thomas W. Miller explains essential concepts, principles, and theory in the context of real-world applications. Building on Miller's pioneering program, Marketing Data Science thoroughly addresses segmentation, target marketing, brand and product positioning, new product development, choice modeling, recommender systems, pricing research, retail site selection, demand estimation, sales forecasting, customer retention, and lifetime value analysis. Starting where Miller's widely-praised Modeling Techniques in Predictive Analytics left off, he integrates crucial information and insights that were previously segregated in texts on web analytics, network science, information technology, and programming. Coverage includes: The role of analytics in delivering effective messages on the web Understanding the web by understanding its hidden structures Being recognized on the web – and watching your own competitors Visualizing networks and understanding communities within them Measuring sentiment and making recommendations Leveraging key data science methods: databases/data preparation, classical/Bayesian statistics, regression/classification, machine learning, and text analytics Six complete case studies address exceptionally relevant issues such as: separating legitimate email from spam; identifying legally-relevant information for lawsuit discovery; gleaning insights from anonymous web surfing data, and more. This text's extensive set of web and network problems draw on rich public-domain data sources; many are accompanied by solutions in Python and/or R. Marketing Data Science will be an invaluable resource for all students, faculty, and professional marketers who want to use business analytics to improve marketing performance.

Marketing Analytics

Author: Wayne L. Winston
Publisher: John Wiley & Sons
ISBN: 9781118417300
Release Date: 2014-01-08
Genre: Computers

Helping tech-savvy marketers and data analysts solve real-world business problems with Excel Using data-driven business analytics to understand customers and improve results is a great idea in theory, but in today's busy offices, marketers and analysts need simple, low-cost ways to process and make the most of all that data. This expert book offers the perfect solution. Written by data analysis expert Wayne L. Winston, this practical resource shows you how to tap a simple and cost-effective tool, Microsoft Excel, to solve specific business problems using powerful analytic techniques—and achieve optimum results. Practical exercises in each chapter help you apply and reinforce techniques as you learn. Shows you how to perform sophisticated business analyses using the cost-effective and widely available Microsoft Excel instead of expensive, proprietary analytical tools Reveals how to target and retain profitable customers and avoid high-risk customers Helps you forecast sales and improve response rates for marketing campaigns Explores how to optimize price points for products and services, optimize store layouts, and improve online advertising Covers social media, viral marketing, and how to exploit both effectively Improve your marketing results with Microsoft Excel and the invaluable techniques and ideas in Marketing Analytics: Data-Driven Techniques with Microsoft Excel.

Customer and Business Analytics

Author: Daniel S. Putler
Publisher: CRC Press
ISBN: 9781466503984
Release Date: 2012-05-07
Genre: Business & Economics

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 text is ideal for students in customer and business analytics or applied data mining as well as professionals in small- to medium-sized organizations. The book offers an intuitive understanding of how different analytics algorithms work. Where necessary, the authors explain the underlying mathematics in an accessible manner. Each technique presented includes a detailed tutorial that enables hands-on experience with real data. The authors also discuss issues often encountered in applied data mining projects and present the CRISP-DM process model as a practical framework for organizing these projects. Showing how data mining can improve the performance of organizations, this book and its R-based software provide the skills and tools needed to successfully develop advanced analytics capabilities.

R for Business Analytics

Author: A Ohri
Publisher: Springer Science & Business Media
ISBN: 9781461443421
Release Date: 2012-09-14
Genre: BUSINESS & ECONOMICS

R for Business Analytics looks at some of the most common tasks performed by business analysts and helps the user navigate the wealth of information in R and its 4000 packages. With this information the reader can select the packages that can help process the analytical tasks with minimum effort and maximum usefulness. The use of Graphical User Interfaces (GUI) is emphasized in this book to further cut down and bend the famous learning curve in learning R. This book is aimed to help you kick-start with analytics including chapters on data visualization, code examples on web analytics and social media analytics, clustering, regression models, text mining, data mining models and forecasting. The book tries to expose the reader to a breadth of business analytics topics without burying the user in needless depth. The included references and links allow the reader to pursue business analytics topics. This book is aimed at business analysts with basic programming skills for using R for Business Analytics. Note the scope of the book is neither statistical theory nor graduate level research for statistics, but rather it is for business analytics practitioners. Business analytics (BA) refers to the field of exploration and investigation of data generated by businesses. Business Intelligence (BI) is the seamless dissemination of information through the organization, which primarily involves business metrics both past and current for the use of decision support in businesses. Data Mining (DM) is the process of discovering new patterns from large data using algorithms and statistical methods. To differentiate between the three, BI is mostly current reports, BA is models to predict and strategize and DM matches patterns in big data. The R statistical software is the fastest growing analytics platform in the world, and is established in both academia and corporations for robustness, reliability and accuracy. The book utilizes Albert Einstein’s famous remarks on making things as simple as possible, but no simpler. This book will blow the last remaining doubts in your mind about using R in your business environment. Even non-technical users will enjoy the easy-to-use examples. The interviews with creators and corporate users of R make the book very readable. The author firmly believes Isaac Asimov was a better writer in spreading science than any textbook or journal author.

Business Analytics Using R A Practical Approach

Author: Umesh R Hodeghatta
Publisher: Apress
ISBN: 9781484225141
Release Date: 2016-12-27
Genre: Computers

Learn the fundamental aspects of the business statistics, data mining, and machine learning techniques required to understand the huge amount of data generated by your organization. This book explains practical business analytics through examples, covers the steps involved in using it correctly, and shows you the context in which a particular technique does not make sense. Further, Practical Business Analytics using R helps you understand specific issues faced by organizations and how the solutions to these issues can be facilitated by business analytics. This book will discuss and explore the following through examples and case studies: An introduction to R: data management and R functions The architecture, framework, and life cycle of a business analytics project Descriptive analytics using R: descriptive statistics and data cleaning Data mining: classification, association rules, and clustering Predictive analytics: simple regression, multiple regression, and logistic regression This book includes case studies on important business analytic techniques, such as classification, association, clustering, and regression. The R language is the statistical tool used to demonstrate the concepts throughout the book. What You Will Learn • Write R programs to handle data • Build analytical models and draw useful inferences from them • Discover the basic concepts of data mining and machine learning • Carry out predictive modeling • Define a business issue as an analytical problem Who This Book Is For Beginners who want to understand and learn the fundamentals of analytics using R. Students, managers, executives, strategy and planning professionals, software professionals, and BI/DW professionals.

Applied Conjoint Analysis

Author: Vithala R. Rao
Publisher: Springer Science & Business Media
ISBN: 9783540877530
Release Date: 2014-02-20
Genre: Business & Economics

Conjoint analysis is probably the most significant development in marketing research in the past few decades. It can be described as a set of techniques ideally suited to studying customers’ decision-making processes and determining tradeoffs. Though this book is oriented towards methods and applications of conjoint analysis in marketing, conjoint methods are also applicable for other business and social sciences. After an introduction to the basic ideas of conjoint analysis the book describes the steps involved in designing a ratings-based conjoint study, it covers various methods for estimating partworth functions from preference ratings data, and dedicates a chapter on methods of design and analysis of conjoint-based choice experiments, where choice is measured directly. Chapter 5 describes several methods for handling a large number of attributes. Chapters 6 through 8 discuss the use of conjoint analysis for specific applications like product and service design or product line decisions, product positioning and market segmentation decisions, and pricing decisions. Chapter 9 collates miscellaneous applications of marketing mix including marketing resource allocation or store location decisions. Finally, Chapter 10 reviews more recent developments in experimental design and data analysis and presents an assessment of future developments.

Cutting edge Marketing Analytics

Author: Rajkumar Venkatesan
Publisher: Pearson Education
ISBN: 9780133552522
Release Date: 2014
Genre: Business & Economics

Master practical strategic marketing analysis through real-life case studies and hands-on examples. In Cutting Edge Marketing Analytics, three pioneering experts integrate all three core areas of marketing analytics: statistical analysis, experiments, and managerial intuition. They fully detail a best-practice marketing analytics methodology, augmenting it with case studies that illustrate the quantitative and data analysis tools you'll need to allocate resources, define optimal marketing mixes; perform effective analysis of customers and digital marketing campaigns, and create high-value dashboards and metrics. For each marketing problem, the authors help you: Identify the right data and analytics techniques Conduct the analysis and obtain insights from it Outline what-if scenarios and define optimal solutions Connect your insights to strategic decision-making Each chapter contains technical notes, statistical knowledge, case studies, and real data you can use to perform the analysis yourself. As you proceed, you'll gain an in-depth understanding of: The real value of marketing analytics How to integrate quantitative analysis with managerial sensibility How to apply linear regression, logistic regression, cluster analysis, and Anova models The crucial role of careful experimental design For all marketing professionals specializing in marketing analytics and/or business intelligence; and for students and faculty in all graduate-level business courses covering Marketing Analytics, Marketing Effectiveness, or Marketing Metrics

New Methods of Market Research and Analysis

Author: G. Scott Erickson
Publisher: Edward Elgar Publishing
ISBN: 9781786432698
Release Date: 2017-10-27
Genre:

New Methods of Market Research and Analysis prepares readers for the new reality posed by big data and marketing analytics. While connecting to traditional research approaches such as surveys and focus groups, this book shows how new technologies and new analytical capabilities are rapidly changing the way marketers obtain and process their information. In particular, the prevalence of big data systems always monitoring key performance indicators, trends toward more research using observation or observation and communication together, new technologies such as mobile, apps, geo-locators, and others, as well as the deep analytics allowed by cheap data processing and storage are all covered and placed in context. This book can be used as a supplement to a traditional marketing research text or on its own.

Predictive Marketing

Author: Omer Artun
Publisher: John Wiley & Sons
ISBN: 9781119037330
Release Date: 2015-08-06
Genre: Business & Economics

Make personalized marketing a reality with this practical guide to predictive analytics Predictive Marketing is a predictive analytics primer for organizations large and small, offering practical tips and actionable strategies for implementing more personalized marketing immediately. The marketing paradigm is changing, and this book provides a blueprint for navigating the transition from creative- to data-driven marketing, from one-size-fits-all to one-on-one, and from marketing campaigns to real-time customer experiences. You'll learn how to use machine-learning technologies to improve customer acquisition and customer growth, and how to identify and re-engage at-risk or lapsed customers by implementing an easy, automated approach to predictive analytics. Much more than just theory and testament to the power of personalized marketing, this book focuses on action, helping you understand and actually begin using this revolutionary approach to the customer experience. Predictive analytics can finally make personalized marketing a reality. For the first time, predictive marketing is accessible to all marketers, not just those at large corporations — in fact, many smaller organizations are leapfrogging their larger counterparts with innovative programs. This book shows you how to bring predictive analytics to your organization, with actionable guidance that get you started today. Implement predictive marketing at any size organization Deliver a more personalized marketing experience Automate predictive analytics with machine learning technology Base marketing decisions on concrete data rather than unproven ideas Marketers have long been talking about delivering personalized experiences across channels. All marketers want to deliver happiness, but most still employ a one-size-fits-all approach. Predictive Marketing provides the information and insight you need to lift your organization out of the campaign rut and into the rarefied atmosphere of a truly personalized customer experience.

Review of Marketing Research

Author: Naresh K. Malhotra
Publisher: Emerald Group Publishing
ISBN: 9780857247285
Release Date: 2009-12-01
Genre: Business & Economics

Contains articles by the marketing field's researchers and scholars. This title presents a view of the marketing research methodologies.

The R Book

Author: Michael J. Crawley
Publisher: John Wiley & Sons
ISBN: 9781118448960
Release Date: 2012-11-07
Genre: Mathematics

Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research. This edition: Features full colour text and extensive graphics throughout. Introduces a clear structure with numbered section headings to help readers locate information more efficiently. Looks at the evolution of R over the past five years. Features a new chapter on Bayesian Analysis and Meta-Analysis. Presents a fully revised and updated bibliography and reference section. Is supported by an accompanying website allowing examples from the text to be run by the user. Praise for the first edition: ‘…if you are an R user or wannabe R user, this text is the one that should be on your shelf. The breadth of topics covered is unsurpassed when it comes to texts on data analysis in R.’ (The American Statistician, August 2008) ‘The High-level software language of R is setting standards in quantitative analysis. And now anybody can get to grips with it thanks to The R Book…’ (Professional Pensions, July 2007)

Marketing Analytics

Author: Mike Grigsby
Publisher: Kogan Page Publishers
ISBN: 9780749474188
Release Date: 2015-06-03
Genre: Business & Economics

Marketing Analytics arms business analysts and marketers with the marketing science understanding and techniques they need to solve real-world marketing problems, from pulling a targeted list and segmenting data to testing campaign effectiveness and forecasting demand. Assuming no prior knowledge, this book outlines everything practitioners need to 'do' marketing science and demonstrate value to their organization. It introduces concepts relating to statistics, marketing strategy and consumer behaviour and then works through a series of marketing problems in a straightforward, jargon-free way. It demonstrates solutions for various data modelling scenarios and includes full workings and critical analyses to reinforce the key concepts. By starting with the marketing problem and then sharing a series of data modelling options on how to solve it, Marketing Analytics both makes marketing science accessible for beginners and aids the more seasoned practitioner in getting to grips with the trickier technical aspects of data analytics to refine their marketing skills and toolkit and compete more effectively in the marketplace. Online supporting resources for this book include a bank of test questions as well as data sets relating to a number of chapters. About the series: The Marketing Science series makes difficult topics accessible to marketing students and practitioners by grounding them in business reality. Each book is written by an expert in the field and includes case studies and illustrations enabling marketers to gain confidence in applying the tools and techniques and in commissioning external research.