Data Analytics for Business: Lessons for Sales, Marketing, and Strategy
Book information
Description
Interest in applying analytics, machine learning, and artificial intelligence to sales and marketing has grown dramatically, with no signs of slowing down. This book provides essential guidance to apply advanced analytics and data mining techniques to real-world business applications. The foundation of this text is the author’s 20-plus years of developing and delivering big data and artificial intelligence solutions across multiple industries: financial services, pharmaceuticals, consumer packaged goods, media, and retail. He provides guidelines and summarized cases for those studying or working in the fields of data science, data engineering, and business analytics. The book also offers a distinctive style: a series of essays, each of which summarizes a critical lesson or provides a step-by-step business process, with specific examples of successes and failures. Sales and marketing executives, project managers, business and engineering professionals, and graduate students will find this clear and comprehensive book the ideal companion when navigating the complex world of big data analytics. Cover Half Title Title Page Copyright Page Table of Contents About the Author Foreword Acknowledgements Part I: Organizational Design Principles 1 Linking Business Challenges to Big Data Solutions 2 Selling the Big Data Analytics Initiative 3 Organizational Structures for Advanced Analytics 4 Lessons Learned Managing Big Data Departments Part II: Analytics Business Applications 5 Segmentation: Categorizing Your Customers 6 Targeting: Getting it “Right” 7 Campaign Measurement with Learning Objectives 8 Strategic Text Mining 9 Predictive Modeling for Business Part III: Implementation and Delivery 10 Privacy Considerations for Big Data Analytics 11 Delivering Results with Actionable Insights 12 Scalability and Long-Term Success References Index
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