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Marketing Analytics

Book Description

Learn about marketing science techniques and how to apply them without fear to compete more effectively in the marketplace.

Table of Contents

  1. Cover page
  2. Praise for marketing analytics
  3. Title page
  4. Imprint
  5. Table of contents
  6. Foreword
  7. Preface
  8. Introduction
  9. PART ONE Overview
    1. 01 A (little) statistical review
      1. Measures of central tendency
      2. Measures of dispersion
      3. The normal distribution
      4. Relations among two variables: covariance and correlation
      5. Probability and the sampling distribution
      6. Conclusion
      7. Checklist: You’ll be the smartest person in the room if you…
    2. 02 Brief principles of consumer behaviour and marketing strategy
      1. Introduction
      2. Consumer behaviour as the basis for marketing strategy
      3. Overview of consumer behaviour
      4. Overview of marketing strategy
      5. Conclusion
      6. Checklist: You’ll be the smartest person in the room if you…
  10. PART TWO Dependent variable techniques
    1. 03 Modelling dependent variable techniques (with one equation): what are the things that drive demand?
      1. Introduction
      2. Dependent equation type vs inter-relationship type statistics
      3. Deterministic vs probabilistic equations
      4. Business case
      5. Results applied to business case
      6. Modelling elasticity
      7. Technical notes
      8. Highlight: Segmentation and elasticity modelling can maximize revenue in a retail/medical clinic chain: field test results
      9. Abstract
      10. The problem and some background
      11. Description of the data set
      12. First: segmentation
      13. Then: elasticity modelling
      14. Last: test vs control
      15. Discussion
      16. Conclusion
      17. Checklist: You’ll be the smartest person in the room if you…
    2. 04 Who is most likely to buy and how do I target?
      1. Introduction
      2. Conceptual notes
      3. Business case
      4. Results applied to the model
      5. Lift charts
      6. Using the model – collinearity overview
      7. Variable diagnostics
      8. Highlight: Using logistic regression for market basket analysis
      9. Abstract
      10. What is a market basket?
      11. Logistic regression
      12. How to estimate/predict the market basket
      13. Conclusion
      14. Checklist: You’ll be the smartest person in the room if you…
    3. 05 When are my customers most likely to buy?
      1. Introduction
      2. Conceptual overview of survival analysis
      3. Business case
      4. More about survival analysis
      5. Model output and interpretation
      6. Conclusion
      7. Highlight: Lifetime value: how predictive analysis is superior to descriptive analysis
      8. Abstract
      9. Descriptive analysis
      10. Predictive analysis
      11. An example
      12. Checklist: You’ll be the smartest person in the room if you…
    4. 06 Modelling dependent variable techniques (with more than one equation)
      1. Introduction
      2. What are simultaneous equations?
      3. Why go to the trouble of using simultaneous equations?
      4. Desirable properties of estimators
      5. Business case
      6. Conclusion
      7. Checklist: You’ll be the smartest person in the room if you…
  11. PART THREE Inter-relationship techniques
    1. 07 Modelling inter-relationship techniques: what does my (customer) market look like?
      1. Introduction
      2. Introduction to segmentation
      3. What is segmentation? What is a segment?
      4. Why segment? Strategic uses of segmentation
      5. The four Ps of strategic marketing
      6. Criteria for actionable segmentation
      7. A priori or not?
      8. Conceptual process
      9. Checklist: You’ll be the smartest person in the room if you…
    2. 08 Segmentation: tools and techniques
      1. Overview
      2. Metrics of successful segmentation
      3. General analytic techniques
      4. Business case
      5. Analytics
      6. Comments/details on individual segments
      7. K-means compared to LCA
      8. Highlight: Why Go Beyond RFM?
      9. Abstract
      10. What is RFM?
      11. What is behavioural segmentation?
      12. What does behavioural segmentation provide that RFM does not?
      13. Conclusion
      14. Segmentation techniques
      15. Checklist: You’ll be the smartest person in the room if you…
  12. PART FOUR Other
    1. 09 Marketing research
      1. Introduction
      2. How is survey data different than database data?
      3. Missing value imputation
      4. Combating respondent fatigue
      5. A far too brief account of conjoint analysis
      6. Structural equation modelling (SEM)
      7. Checklist: You’ll be the smartest person in the room if you…
    2. 10 Statistical testing: how do I know what works?
      1. Everyone wants to test
      2. Sample size equation: use the lift measure
      3. A/B testing and full factorial differences
      4. Business case
      5. Checklist: You’ll be the smartest person in the room if you…
  13. PART FIVE Capstone
    1. 11 Capstone: focusing on digital analytics
      1. Introduction
      2. Modelling engagement
      3. Business case
      4. Model conception
      5. How do I model multiple channels?
      6. Conclusion
  14. PART SIX Conclusion
    1. 12 The Finale: what should you take away from this? Any other stories/soap box rants?
      1. What things have I learned that I’d like to pass on to you?
      2. What other things should you take away from all this?
  15. Glossary
  16. Bibliography and further reading
  17. Index