Marketing analytics : a practical guide to real marketing science /

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Bibliographic Details
Author / Creator:Grigsby, Mike.
Imprint:London : Philadelphia : Kogan Page, 2015.
Description:1 online resource.
Language:English
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/10299467
Hidden Bibliographic Details
ISBN:9780749474188 (electronic bk.)
0749474181 (electronic bk.)
9780749474171 (paperback)
0749474173 (paperback)
Notes:Description based on print version record.
Other form:Original 9780749474171 0749474173

MARC

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245 1 0 |a Marketing analytics :  |b a practical guide to real marketing science /  |c Mike Grigsby. 
264 1 |a London : Philadelphia :  |b Kogan Page,  |c 2015. 
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505 8 |a 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 . 
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