Includes bibliographical references and index.

Section - 00: Introduction to marketing analytics;Section - PART ONE: Overview – how can marketing analytics help you?;Section - 01: A brief statistics review;Section - 02: Brief principles of consumer behaviour and marketing strategy;Section - 03: What is an insight?;Section - PART TWO: Dependent variable techniques;Section - 04: What drives demand? Modelling dependent variable techniques;Section - 05: Who is most likely to buy and how do I target them?;Section - 06: When are my customers most likely to buy?;Section - 07: Panel regression – how to use a cross-sectional time series;Section - 08: Systems of equations for modelling dependent variable techniques;Section - PART THREE: Inter-relationship techniques;Section - 09: What does my (customer) market look like? Modelling inter-relationship techniques ;Section - 10: Segmentation – tools and techniques;Section - PART FOUR: More important topics for everyday marketing;Section - 11: Statistical testing – how do I know what works?;Section - 12: Implementing Big Data and Big Data analytics;Section - PART FIVE: Conclusion;Section - 13: The finale – what should you take away from this?;Section - 14: Glossary;

Who is most likely to buy and what is the best way to target them? How can businesses improve strategy without identifying the key influencing factors? The second edition of Marketing Analytics enables marketers and business analysts 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, this book offers a welcome handbook on how statistics, consumer analytics and modelling can be put to optimal use.

The fully revised second edition of Marketing Analytics includes three new chapters on big data analytics, insights and panel regression, including how to collect, separate and analyze big data. All of the advanced tools and techniques for predictive analytics have been updated, translating models such as tobit analysis for customer lifetime value into everyday use. Whether an experienced practitioner or having no prior knowledge, methodologies are simplified to ensure the more complex aspects of data and analytics are fully accessible for any level of application. Complete with downloadable data sets and test bank resources, this book supplies a concrete foundation to optimize marketing analytics for day-to-day business advantage.

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