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Essentials of marketing analytics / Joseph F. Hair, Jr., University of South Alabama, Dana E. Harrison, East Tennessee State University, Haya Ajjan, Elon University.

By: Hair, Joseph F., Jr, 1944- [author.].
Contributor(s): Harrison, Dana E [author.] | Ajjan, Haya [author.].
Publisher: New York, NY, USA : McGraw Hill LLC, 2022Edition: International student edition.Description: xviii, 462 pages : color illustrations ; 26 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 9781260597745.Subject(s): Marketing research | MarketingAdditional physical formats: Online version:: Essentials of marketing analytics, 1eDDC classification: 658.83 H12
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 Analytics
Summary: "We developed this new book with enthusiasm and great optimism. Marketing analytics is an exciting field to study, and there are numerous emerging opportunities for students at the undergraduate level, and particularly at the master's level. We live in a global, highly competitive, rapidly changing world that is increasingly influenced by digital data, expanded analytical capabilities, information technology, social media, artificial intelligence, and many other recent developments. We believe this book will become the premier source for new and essential knowledge in data analytics, particularly for situations related to marketing decision making that can benefit from marketing analytics, which is likely 80 percent of all challenges faced by organizations"-- Provided by publisher.
Item type Current location Collection Call number Status Date due Barcode
Books Books College Library
General Circulation Section
GC GC 658.83 H12 2022 (Browse shelf) Available HNU004214

Includes bibliographical references and index.

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 Analytics

"We developed this new book with enthusiasm and great optimism. Marketing analytics is an exciting field to study, and there are numerous emerging opportunities for students at the undergraduate level, and particularly at the master's level. We live in a global, highly competitive, rapidly changing world that is increasingly influenced by digital data, expanded analytical capabilities, information technology, social media, artificial intelligence, and many other recent developments. We believe this book will become the premier source for new and essential knowledge in data analytics, particularly for situations related to marketing decision making that can benefit from marketing analytics, which is likely 80 percent of all challenges faced by organizations"-- Provided by publisher.

College of Business and Accountancy Bachelor of Science in Business Administration Major in Marketing Management

Text in English

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