Marketing analytics : a practical guide to real marketing science /
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| Author / Creator: | Grigsby, Mike. |
|---|---|
| Imprint: | London : Philadelphia : Kogan Page, 2015. |
| Description: | 1 online resource. |
| Language: | English |
| Subject: | Marketing research. Marketing. Marketing. Marketing research. |
| Format: | E-Resource Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/10299467 |
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| 100 | 1 | |a Grigsby, Mike. |0 http://id.loc.gov/authorities/names/n2015026358 |1 http://viaf.org/viaf/315594194 | |
| 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. | |
| 300 | |a 1 online resource. | ||
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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 . | |
| 588 | |a Description based on print version record. | ||
| 650 | 0 | |a Marketing research. |0 http://id.loc.gov/authorities/subjects/sh85081350 | |
| 650 | 0 | |a Marketing. |0 http://id.loc.gov/authorities/subjects/sh85081333 | |
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| 650 | 7 | |a Marketing research. |2 fast |0 http://id.worldcat.org/fast/fst01010284 | |
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