Data Analytics for Business

Lessons for Sales, Marketing, and Strategy
1. Auflage 2022
ISBN: 978-0-367-28148-9
Verlag: Taylor & Francis Ltd

Buch, Englisch, 178 Seiten, Format (B × H): 150 mm x 225 mm, Gewicht: 270 g

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.

Autoren/Hrsg.

Haimowitz, Ira J.

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Management Entscheidungsfindung
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Wirtschaftsprognose
• Wirtschaftswissenschaften Betriebswirtschaft Marktforschung
• Wirtschaftswissenschaften Betriebswirtschaft Management Projektmanagement
• Wirtschaftswissenschaften Betriebswirtschaft Management Wissensmanagement

Inhaltsverzeichnis

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 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 Implementation and Delivery 10. Privacy Considerations for Big Data Analytics 11. Delivering Results with Actionable Insights 12. Scalability and Long Term Success

Über Autor(innen)

Ira J. Haimowitz, Ph.D. is a product management consultant currently specializing in developing and delivering strategy and analytics solutions for the life sciences sector, with over 20 years' experience across industries.