Marketing analytics [electronic resource] : a practical guide to improving consumer insights using data techniques / Second edition

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자료유형	e-Book
서명/저자사항	Marketing analytics [electronic resource]: a practical guide to improving consumer insights using data techniques / Mike Grigsby.
개인저자	Grigsby, Mike, author.
판사항	Second edition.
발행사항	London ; New York: Kogan Page, 2018.
형태사항	1 online resource.
기타형태 저록	Print version: Grigsby, Mike. Marketing analytics. Second edition. London ; New York : Kogan Page, 2018 9780749482169
ISBN	9780749482176 0749482176
서지주기	Includes bibliographical references and index.
내용주기	Cover; Contents; Foreword to the first edition; Foreword to the second edition; Preface; Introduction to marketing analytics; PART ONE Overview -- how can marketing analytics help you?; 01 A brief statistics review; Measures of central tendency; Measures of dispersion; The normal distribution; Confidence intervals; Relations among two variables: covariance and correlation; Probability and the sampling distribution; Conclusion; Checklist: You'll be the smartest person in the room if you...; 02 Brief principles of consumer behaviour and marketing strategy; Introduction Consumer behaviour as the basis for marketing strategyOverview of consumer behaviour; Overview of marketing strategy; Conclusion; Checklist: You'll be the smartest person in the room if you...; 03 What is an insight?; Introduction; Insights tend not to be used by executives; Is this an insight?; So, what is an insight?; Ultimately, an insight is about action-ability; Checklist: You'll be the smartest person in the room if you...; PART TWO Dependent variable techniques; 04 What drives demand? Modelling dependent variable techniques; Introduction Dependent equation type vs inter-relationship type statisticsDeterministic vs probabilistic equations; Business case; Results applied to business case; Modelling elasticity; Technical notes; Highlight: Segmentation and elasticity modelling can maximize revenue in a retail/medical clinic chain:field test results; Abstract; The problem and some background; Description of the dataset; First: segmentation; Then: elasticity modelling; Last: test vs control; Discussion; Conclusion; Checklist: You'll be the smartest person in the room if you...; 05 Who is most likely to buy and how do I target them? IntroductionConceptual notes; Business case; Results applied to the model; Lift charts; Using the model -- collinearity overview; Variable diagnostics; Highlight: Using logistic regression for market basket analysis; Abstract; What is a market basket?; Logistic regression; How to estimate/predict the market basket; Conclusion; Checklist: You'll be the smartest person in the room if you...; 06 When are my customers most likely to buy?; Introduction; Conceptual overview of survival analysis; Business case; More about survival analysis; Model output and interpretation; Conclusion Highlight: Lifetime value: how predictive analysis is superior to descriptive analysisAbstract; Descriptive analysis; Predictive analysis; An example; Checklist: You'll be the smartest person in the room if you...; 07 Panel regression -- how to use a cross-sectional time series; Introduction; What is panel regression?; Panel regression: details; Business case; Insights about marcom (direct mail, e-mail and SMS); Insights about time period (quarters); Insights about cross sections (counties); Conclusion; Checklist: You'll be the smartest person in the room if you...
요약	Understand how to apply marketing science techniques fearlessly, to improve consumer insights and compete more effectively in the marketplace.
일반주제명	Marketing research. Marketing. Marketing. Marketing research. BUSINESS & ECONOMICS / Industrial Management. BUSINESS & ECONOMICS / Management. BUSINESS & ECONOMICS / Management Science. BUSINESS & ECONOMICS / Organizational Behavior.
분류기호(DDC)	658.83
언어	영어
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