Marketing Analytics: A Practical Guide to Improving Consumer Insights Using Data Techniques, Third Edition
- 4h 46m
- Mike Grigsby
- Kogan Page
- 2022
Who is most likely to buy and what is the best way to target them? How can I use both consumer analytics and modelling to improve the impact of marketing campaigns? Marketing Analytics takes you step-by-step through these areas and more.
Marketing Analytics enables you to leverage predictive techniques to measure and improve marketing performance. By exploring real-world marketing challenges, it provides clear, jargon-free explanations on how to apply different analytical models for each purpose. From targeted list creation and data segmentation, to testing campaign effectiveness, pricing structures and forecasting demand, it offers a complete resource for how statistics, consumer analytics and modelling can be put to optimal use.
This revised and updated third edition of Marketing Analytics contains new material on forecasting, customer touchpoints modelling, and a new focus on customer loyalty. With accessible language throughout, methodologies are simplified to ensure the more complex aspects of data and analytics are fully accessible for any level of application. Supported by a glossary of key terms and supporting resources consisting of datasets, presentation slides for each chapter and a test bank of self-test question, this book supplies a concrete foundation for optimizing marketing analytics for day-to-day business advantage.
About the Author
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.
In this Book
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Introduction
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Overview of Statistics
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Consumer Behaviour and Marketing Strategy
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What Is an Insight?
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Modelling Demand and Elasticity
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Polynomial Distributed Lags
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Using Poisson Regression
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Logistic Regression and Market Basket Analysis
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Survival Modelling and Lifetime Value
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Panel Regression and Same Store Sales
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Introduction to Forecasting
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Simultaneous Equations
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Principal Components and Factor Analysis
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Segmentation Overview
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Tools of Segmentation
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Modelling Marcom Value
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Media Mix Modelling
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Overview of Loyalty
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Loyalty with SEM
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The Customer Loyalty Journey
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Statistical Testing
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Introduction to Big Data
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Conclusion—The Finale
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References
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Further Reading
