Confidently apply marketing analytics techniques to improve consumer insights and marketing performance, so you can compete more effectively in the marketplace.
Confidently apply marketing analytics techniques to improve consumer insights and marketing performance, so you can compete more effectively in the marketplace.
Mike Grigsby, based in Orlando, Florida, has more than 30 years' experience in the field of marketing analytics. He was formerly vice president of customer insights and advanced analytics at Brierley and Partners and of strategic business analysis and advanced analytics at Targetbase and has also held leadership positions at Hewlett-Packard and Gap. Previously an adjunct professor at the University of Texas at Dallas, he taught analytics at both graduate and undergraduate levels. He is the author of Advanced Customer Analytics, also published by Kogan Page.
Inhaltsangabe
Section 00: Introduction; Section PART ONE: How can marketing analytics help you?; Chapter 01: Overview of statistics; Chapter 02: Consumer behaviour and marketing strategy; Chapter 03: What is an insight?; Section PART TWO: Dependent variable techniques; Chapter 04: Modelling demand and elasticity; Chapter 05: Polynomial distributed lags; Chapter 06: Using Poisson regression; Chapter 07: Logistic regression and market basket analysis; Chapter 08: Survival modelling and lifetime value; Chapter 09: Panel regression and same store sales; Chapter 10: Introduction to forecasting; Section PART THREE: Interrelationship techniques; Chapter 11: Simultaneous equations; Chapter 12: Principal components and factor analysis; Chapter 13: Segmentation overview; Chapter 14: Tools of segmentation; Section PART FOUR: Focus on media and loyalty; Chapter 15: Modelling marcom value; Chapter 16: Media mix modelling; Chapter 17: Overview of loyalty; Chapter 18: Loyalty with SEM; Chapter 19: The customer loyalty journey; Section PART FIVE: More important topics for everyday marketing; Chapter 20: Statistical testing; Chapter 21: Introduction to Big Data; Chapter 22: Conclusion The finale; Chapter 23: References; Chapter 24: Further reading;
Section 00: Introduction; Section PART ONE: How can marketing analytics help you?; Chapter 01: Overview of statistics; Chapter 02: Consumer behaviour and marketing strategy; Chapter 03: What is an insight?; Section PART TWO: Dependent variable techniques; Chapter 04: Modelling demand and elasticity; Chapter 05: Polynomial distributed lags; Chapter 06: Using Poisson regression; Chapter 07: Logistic regression and market basket analysis; Chapter 08: Survival modelling and lifetime value; Chapter 09: Panel regression and same store sales; Chapter 10: Introduction to forecasting; Section PART THREE: Interrelationship techniques; Chapter 11: Simultaneous equations; Chapter 12: Principal components and factor analysis; Chapter 13: Segmentation overview; Chapter 14: Tools of segmentation; Section PART FOUR: Focus on media and loyalty; Chapter 15: Modelling marcom value; Chapter 16: Media mix modelling; Chapter 17: Overview of loyalty; Chapter 18: Loyalty with SEM; Chapter 19: The customer loyalty journey; Section PART FIVE: More important topics for everyday marketing; Chapter 20: Statistical testing; Chapter 21: Introduction to Big Data; Chapter 22: Conclusion The finale; Chapter 23: References; Chapter 24: Further reading;
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