Marketing Database Analytics: Transforming Data for Competitive Advantage / Edition 1

by Andrew D. Banasiewicz

Overview

Marketing Database Analytics presents a step-by-step process for understanding and interpreting data in order to gain insights to drive business decisions. One of the core elements of measuring marketing effectiveness is through the collection of appropriate data, but this data is nothing but numbers unless it is analyzed meaningfully.

Focusing specifically on quantitative marketing metrics, the book:

• Covers the full spectrum of marketing analytics, from the initial data setup and exploration, to segmentation, behavioral predictions and impact quantification
• Establishes the importance of database analytics, integrating both business and marketing practice
• Provides a theoretical framework that explains the concepts and delivers techniques for analyzing data
• Includes cases and exercises to guide students’ learning

Banasiewicz integrates his knowledge from both his academic training and professional experience, providing a thorough, comprehensive approach that will serve graduate students of marketing research and analytics well.

Product Details

ISBN-13:	9780415657884
Publisher:	Taylor & Francis
Publication date:	05/02/2013
Edition description:	New Edition
Pages:	400
Product dimensions:	6.88(w) x 9.69(h) x (d)

About the Author

Andrew Banasiewicz is a lecturer at the School of Management at Boston University, USA. He has held senior level positions in marketing, database management and risk management organizations, and has authored two other books, as well as numerous articles. For a more detailed biography, visit http://msmonline.bu.edu/faculty/andrew-banasiewicz

Table of Contents

1. The Informational Advantage 2. The Marketing Database Analytics Process Part I: Need Identification 3. Organizational Objectives and Informational Needs 4. Skills and Tools Part II: Knowledge Creation 5. Analytic Planning 6. Data Basics 7. Analytic File Creation 8. Exploratory Data Analyses 9. Segmentation 10. Behavioral Predictions 11. Action-attributable Incrementality 12. Database Scoring 13. From Findings to Knowledge Part III: Dissemination 14. Organizational Knowledge Sharing 15. In Closing