Essentials of Marketing Analytics
by: Joseph Hair (Author), Dana E. Harrison (Author), Haya Ajjan (Author)
Publisher finelybook 出版社: McGraw Hill; (February 18, 2021)
Language 语言: English
Print Length 页数: 480 pages
ISBN-10: 1264263600
ISBN-13: 9781264263608
Book Description
The starting point in learning marketing analytics is to understand the marketing problem. The second is asking the right business question. The data will help you tell the story.
We live in a global, highly competitive, rapidly changing world that is increasingly influenced by digital data, expanded analytical capabilities, information technology, social media and more. The era of Big Data has literally brought about huge amounts of data to review, analyze and solve. Today’s undergraduate and graduate students will need to have a keen understanding of not only the right types of questions to ask, but also the tools available to help answer them. Essentials of Marketing Analytics covers both, in a comprehensive, readable and flexible manner.
Coverage includes the most popular analytics software tools, such as Tableau and Python, as well as a variety of analytical techniques, including but not limited to social network analysis, automated machine learning, neural networking and more. Supported by a robust student and learning package via McGraw Hill Connect, Essentials of Marketing Analytics 1e is the most comprehensive, current, adaptable product on the market!
About the Author
Dana Eckerle Harrison is an Associate Professor of Marketing and Chair for the Department of Management and Marketing at East Tennessee State University. Prior to her work in academia, Dana spent many years assisting software companies in the areas of marketing and sales management. She teaches marketing research, analytics, digital marketing and strategy courses at the undergraduate and graduate level. In 2022, she was the recipient of the College of Business and Technology Research Award and in 2019, received the New Faculty Award recognizing dedication to teaching, research, and service. Her scholarly research has been published in journals such as the Journal of Business Research, the Journal of Product and Brand Management, and the Journal of Marketing Theory and Practice. Her research focuses on the intersection between customer relationship management, business ethics, data quality and governance, and marketing analytics methods. Dana is a co-author on the Essentials of Marketing Analytics, , McGraw-Hill/Irwin, 2021. She currently serves as an associate editor for the Journal of Marketing Theory and Practice, as well as on the Editorial Review Board for the Journal of Business Research and Journal of Marketing Education. Dana continues to be an active member of prominent marketing organizations. She has presented and led panel discussions at conferences such as the Academy of Marketing Science, American Marketing Association, INFORMS Society for Marketing Science, and the Society for Marketing Advances, regarding topics such as artificial intelligence and business ethics, social network analysis, sales management, the impact of analytics techniques and technology on marketing education and practice, the emergence of block chain in marketing, and information governance. Furthermore, she has offered certificate programs on marketing analytics and currently serves as the Program Chair and President-Elect for the Society of Marketing Advances and the Secretary/Treasurer for the Academy of Marketing Science.
Joseph F. Hair, Jr. is Professor of Marketing and the Cleverdon Chair of Business at the University of South Alabama, and Director of the PhD degree program in the Mitchell College of Business. He formerly held the Copeland Endowed Chair of Entrepreneurship at Louisiana State University. In the years 2018–2021, Dr. Hair was recognized by Clarivate Analytics as being in the top 1 percent globally of all Business and Economics professors. He was selected for the award based on citations of his research and scholarly accomplishments, which for his career exceed 302,000. He has published more than 85 editions of his books, including market leaders Multivariate Data Analysis, 8th edition, Cengage Learning, UK, 2019, which has been cited more than 152,000 times; Marketing Research, 6th edition, McGraw-Hill/Irwin, 2023; MKTG/Marketing Principles, 13th edition, Cengage Learning, 2020, used at over 500 universities globally; A Primer in Partial Least Squared Structural Equation Modeling (PLS-SEM), 3rd edition, Sage, 2022; and Essentials of Business Research Methods, 5th edition, Routledge, 2023. In addition to publishing numerous referred manuscripts in academic journals such as Journal of Marketing Research, Journal of Academy of Marketing Science, Journal of Business/Chicago, Journal of Advertising Research, and Journal of Retailing, he has presented executive education and management training programs for numerous companies, has been retained as consultant and expert witness for a wide variety of firms, and is frequently an invited speaker on research methods and multivariate analysis. He is a Distinguished Fellow of the Academy of Marketing Science and the Society for Marketing Advances (SMA) and has served as president of the Academy of Marketing Sciences, the SMA, the Southern Marketing Association, the Association for Healthcare Research, the Southwestern Marketing Association, and the American Institute for Decision Sciences, Southeast Section. Professor Hair was recognized by the Academy of Marketing Science with its Outstanding Marketing Teaching Excellence Award, and the Louisiana State University Entrepreneurship Institute under his leadership was recognized nationally by Entrepreneurship Magazine as one of the top 12 programs in the United States.
Haya Ajjan is an Associate Professor of Management Information Systems, the Sheldon and Christine Gordon Professor in Entrepreneurship, and the Director of the Center for Organizational Analytics at Elon University. Haya joined Elon in 2010 and teaches data analytics courses in the Love School of Business’ undergraduate business, MBA and M.S. in Business Analytics programs. She was instrumental in developing the business analytics undergraduate major and the M.S. in Business Analytics program. Her research focuses on better understanding the impact of technology use on individuals, groups and organizations, and has been published in journals such as Journal of Business Research, European Journal of Operations Research, Business Horizons, Journal of Marketing Analytics, and Journal of Marketing Theory and Practice. Her commitment to infusing technology and innovation into the curriculum resulted in her appointment as Faculty Fellow for Innovation and Assistant to Elon University President Constance Ledoux Book. She also serves as a project lead for Elon’s participation in Apple’s Everyone Can Code initiative. Ajjan received the Love School of Business Dean’s Awards for Scholarship and Service and was named Top 50 Undergraduate Business Professors in the United States. During her tenure at Elon, she founded the Center for Organizational Analytics, Elon NEXT for professional advancement and continuing education studies, and the Elon Innovation Council. She teaches a certificate program on marketing analytics for the Academy of Marketing Science and currently serves as a program co-chair for AIS Special Interest Group in Decision Support and Analytics.
Table of Contents
PART ONE: OVERVIEW OF MARKETING ANALYTICS AND DATA MANAGEMENT
Chapter 1: Introduction to Marketing Analytics
Chapter 2: Data Management
PART TWO: EXPLORING AND VISUALIZING DATA PATTERNS
Chapter 3: Exploratory Data Analysis Using Cognitive Analytics
Chapter 4: Data Visualization
PART THREE: ANALYTICAL METHODS FOR SUPERVISED LEARNING
Chapter 5: Regression Analysis
Chapter 6: Neural Networks
Chapter 7: Automated Machine Learning
PART FOUR: ANALYTICAL METHODS FOR UNSUPERVISED LEARNING
Chapter 8: Cluster Analysis
Chapter 9: Market Basket Analysis
PART FIVE: EMERGING ANALYTICAL APPROACHES
Chapter 10: Natural Language Processing – Text Mining and Sentiment Analysis
Chapter 11: Social Network Analysis
Chapter 12: Web AnalyticsAmazon page
