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.
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;
