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Table of Content

 "Preface    
 Figures   
 Tables    
 Exhibits   
 1 Understanding Markets    
 2 Predicting Consumer Choice    
 3 Targeting Current Customers    
 4 Finding New Customers    
 5 Retaining Customers    
 6 Positioning Products    
 7 Developing New Products    
 8 Promoting Products    
 9 Recommending Products    
 10 Assessing Brands and Prices    
 11 Utilizing Social Networks    
 12 Watching Competitors    
 13 Predicting Sales    
 14 Redefining Marketing Research    
 A Data Science Methods    
 B Marketing Data Sources    
 C Case Studies    
 D Code and Utilities    
 Bibliography   
 Index    
   

Salient Features

The fully-integrated, expert, hands-on guide to predictive analytics and data science for marketing

Fully integrates everything you need to know to address real marketing challenges - including all relevant web analytics, network science, information technology, and programming techniques
 Covers analytics for segmentation, targeting, positioning, pricing, product development, site selection, recommender systems, forecasting, retention, lifetime value analysis, and much more
 Includes multiple examples demonstrated with Python and R
 By Thomas W. Miller, leader of Northwestern's pioneering predictive analytics program, and author of Modeling Techniques in Predictive Analytics"   aData Science