ATU Sligo /ATU St Angela's

go

Amazon cover image
Image from Amazon.com

Marketing analytics : a practical guide to real marketing science /

By: Grigsby, Mike.
Series: Marketing science series.Publisher: London : Philadelphia : Kogan Page, 2015Description: xv, 232 pages : ill. ; 26 cm.Content type: text $2 rdacontent | text Media type: unmediated $2 rdamedia | unmediated Carrier type: volume $2 rdacarrier | volumeISBN: 9780749474171 (paperback); 9780749474171:; 0749474173 (paperback).Subject(s): Visual analytics | Marketing research | MarketingDDC classification: 658.83
Contents:
Machine generated contents note: Foreword -- PrefaceIntroduction Part One: Overview01 A (little) statistical review -- Measures of central tendency -- Measures of dispersion -- The normal distribution -- 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 strategy -- Overview of consumer behaviour -- Overview of marketing strategy -- Conclusion -- Checklist: You'll be the smartest person in the room if you...Part Two Dependent variable techniques 03 Modelling dependent variable techniques (with one equation): what are the things that drive demand? -- Introduction -- Dependent equation type vs inter-relationship type statistics -- Deterministic 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/clinic chain: field test results -- Abstract -- The problem and some background -- Description of the data set -- First: segmentation -- Then: elasticity modelling -- Last: test vs control -- Discussion -- Conclusion -- Checklist: You'll be the smartest person in the room if you...04 Who is most likely to buy and how do I target? -- Introduction -- Conceptual 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...05 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 analysis -- Abstract -- Descriptive analysis -- Predictive analysis -- An example -- Checklist: You'll be the smartest person in the room if you...06 Modelling-dependent variable techniques (with more than one equation) -- Introduction -- What are simultaneous equations? -- Why go to the trouble to use simultaneous equations? -- Desirable properties of estimators -- Business case -- Checklist: You'll be the smartest person in the room if you...Part Three Inter-relationship techniques 07 Modelling inter-relationship techniques: what does my (customer) market look like? -- Introduction -- Introduction to segmentation -- What is segmentation? What is a segment? -- Why segment? Strategic uses of segmentation -- The four Ps of strategic marketing -- Criteria for actionable segmentation -- A priori or not? -- Conceptual process -- Checklist: You'll be the smartest person in the room if you...08 Segmentation tools and techniques -- Overview -- Metrics of successful segmentation -- General analytic techniques -- Business case -- Analytics -- Comments/details on individual segments -- K-means compared to LCA -- Highlight: Why Go Beyond RFM? -- Abstract -- What is RFM? -- What is behavioural segmentation? -- What does behavioural segmentation provide that RFM does not? -- Conclusion -- Sidebar: Segmentation techniques -- Checklist: You'll be the smartest person in the room if you...Part Four Other -- 09 Marketing Research -- Introduction -- How is survey data different than database data? -- Missing value imputation -- Combating respondent fatigue -- A far too brief account of conjoint analysis -- Structural equation modelling (SEM) -- Checklist: You'll be the smartest person in the room if you...10 Statistical testing: how do I know what works? -- Everyone wants to test -- Sample size equation: use the lift measure -- A/B testing and full factorial differences -- Business case -- Checklist: You'll be the smartest person in the room if you...Part Five Capstone 11 Capstone: focusing on digital analytics -- Introduction -- Modelling engagement -- Business case -- Model conception -- How do I model multiple channels? -- ConclusionPart Six Conclusion 12 The Finale: What should you take away from this? Any other stories/soap box rants? -- What things have I learned that I'd like to pass on to you? -- What other things should you take away from all this?Glossary -- Bibliography and further reading -- Index .
Summary: This title arms business analysts and marketers with the marketing science understanding and techniques they need to solve real-world marketing problems, from pulling a targeted list and segmenting data to testing campaign effectiveness and forecasting demand. Assuming no prior knowledge, this book outlines everything practitioners need to 'do' marketing science and demonstrate value to their organization. It introduces concepts relating to statistics, marketing strategy and consumer behaviour and then works through a series of marketing problems in a straightforward, jargon-free way.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Call number Copy number Status Date due Barcode Item holds
Standard Loan Standard Loan ATU Sligo Yeats Library Main Lending Collection 658.83 GRI (Browse shelf(Opens below)) 1 Available 0092518
Total holds: 0

Machine generated contents note: Foreword -- PrefaceIntroduction Part One: Overview01 A (little) statistical review -- Measures of central tendency -- Measures of dispersion -- The normal distribution -- 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 strategy -- Overview of consumer behaviour -- Overview of marketing strategy -- Conclusion -- Checklist: You'll be the smartest person in the room if you...Part Two Dependent variable techniques 03 Modelling dependent variable techniques (with one equation): what are the things that drive demand? -- Introduction -- Dependent equation type vs inter-relationship type statistics -- Deterministic 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/clinic chain: field test results -- Abstract -- The problem and some background -- Description of the data set -- First: segmentation -- Then: elasticity modelling -- Last: test vs control -- Discussion -- Conclusion -- Checklist: You'll be the smartest person in the room if you...04 Who is most likely to buy and how do I target? -- Introduction -- Conceptual 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...05 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 analysis -- Abstract -- Descriptive analysis -- Predictive analysis -- An example -- Checklist: You'll be the smartest person in the room if you...06 Modelling-dependent variable techniques (with more than one equation) -- Introduction -- What are simultaneous equations? -- Why go to the trouble to use simultaneous equations? -- Desirable properties of estimators -- Business case -- Checklist: You'll be the smartest person in the room if you...Part Three Inter-relationship techniques 07 Modelling inter-relationship techniques: what does my (customer) market look like? -- Introduction -- Introduction to segmentation -- What is segmentation? What is a segment? -- Why segment? Strategic uses of segmentation -- The four Ps of strategic marketing -- Criteria for actionable segmentation -- A priori or not? -- Conceptual process -- Checklist: You'll be the smartest person in the room if you...08 Segmentation tools and techniques -- Overview -- Metrics of successful segmentation -- General analytic techniques -- Business case -- Analytics -- Comments/details on individual segments -- K-means compared to LCA -- Highlight: Why Go Beyond RFM? -- Abstract -- What is RFM? -- What is behavioural segmentation? -- What does behavioural segmentation provide that RFM does not? -- Conclusion -- Sidebar: Segmentation techniques -- Checklist: You'll be the smartest person in the room if you...Part Four Other -- 09 Marketing Research -- Introduction -- How is survey data different than database data? -- Missing value imputation -- Combating respondent fatigue -- A far too brief account of conjoint analysis -- Structural equation modelling (SEM) -- Checklist: You'll be the smartest person in the room if you...10 Statistical testing: how do I know what works? -- Everyone wants to test -- Sample size equation: use the lift measure -- A/B testing and full factorial differences -- Business case -- Checklist: You'll be the smartest person in the room if you...Part Five Capstone 11 Capstone: focusing on digital analytics -- Introduction -- Modelling engagement -- Business case -- Model conception -- How do I model multiple channels? -- ConclusionPart Six Conclusion 12 The Finale: What should you take away from this? Any other stories/soap box rants? -- What things have I learned that I'd like to pass on to you? -- What other things should you take away from all this?Glossary -- Bibliography and further reading -- Index .

This title arms business analysts and marketers with the marketing science understanding and techniques they need to solve real-world marketing problems, from pulling a targeted list and segmenting data to testing campaign effectiveness and forecasting demand. Assuming no prior knowledge, this book outlines everything practitioners need to 'do' marketing science and demonstrate value to their organization. It introduces concepts relating to statistics, marketing strategy and consumer behaviour and then works through a series of marketing problems in a straightforward, jargon-free way.

Share