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One of the larger challenges of teaching modeling is the issue of balancing quantitative skill sets with qualitative concepts. Students require familiarity with specific mathematical concepts and formulas in order to perform basic tasks. This is a topic that is being taken very seriously in the discipline. Many companies routinely collect massive amounts of customer data, which requires marketing modelers to translate that data into information that may be used to make fact-based strategic and tactical decisions. Marketers are being challenged to illustrate and demonstrate the financial return and measurement of their actions and marketing dashboards and metrics are becoming more important. This book was itself designed in part from a customer perspective, and each chapter also covers a marketing topic using the optimal methods.
Inhaltsverzeichnis
1. Introduction to Marketing Analytics.
2. Marketing Segmentation and Cluster Analysis.
3. Perceptual Maps and Multi-Dimensional Scaling.
4. New Product Development and Conjoint Analysis.
5. ROI and Market Tests with Experiments and Analysis of Variance.
6. Diffusion Models with Market Sizing, Forecasting, and Customer Lifetime Value.
7. Scanner Data, Brand Choice, Loyalty and Switching with Logit Models and Logistic Regressions, CRM, RFM, and Data-Base Marketing.
8. Customer Satisfaction and Path Models.
9. Word of Mouth and Social Networks.
10. Classic Marketing Models.
Über den Autor / die Autorin
Dawn Iacobucci is the Coca-Cola Distinguished Professor of Marketing and Head of the Marketing Department at the University of Arizona in Tucson. She was previously professor of marketing at the Kellogg School of Management, Northwestern University.
Zusammenfassung
Marketers are being challenged to illustrate and demonstrate the financial return and measurement of their actions and marketing dashboards and metrics are becoming more important. This title covers marketing topics using the optimal methods.
