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Marketing analytics : a practical guide to real marketing science

Author: Mike Grigsby
Publisher: London : Philadelphia : Kogan Page, 2015. ©2015
Series: Marketing science series.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
"Mike Grigsby provides business analysts and marketers with the marketing science understanding and techniques they need to solve real-world marketing challenges, such as pulling a targeted list, segmenting data, testing campaign effectiveness, and forecasting demand.Assuming no prior knowledge, Marketing Analytics introduces concepts relating to statistics, marketing strategy, and consumer behavior and then works
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Grigsby, Mike.
Marketing analytics.
London : Philadelphia : Kogan Page, 2015
(DLC) 2015016002
(OCoLC)907146519
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Mike Grigsby
ISBN: 9780749474188 0749474181
OCLC Number: 910554172
Description: 1 online resource (xvi, 232 pages) : illustrations
Contents: Foreword --
Preface --
Introduction --
Part One Overview --
01 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 modell ing can maximize revenue in a retail/medical 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 of using simultaneous equations? --
Desirable properties of estimators --
Business case --
Conclusion --
Checklist: You'll be the smartest person in the room if you... --
Part Three Inter-relationship techniques --
07 Modelling inter-relationship techniques --
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 RF M? --
Abstract --
What is RFM? --
What is behavioural segmentation? --
What does behavioural segmentation provide that RFM does not? --
Conclusion --
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 --
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? --
Conclusion --
Part 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.
Series Title: Marketing science series.
Responsibility: Mike Grigsby.

Abstract:

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

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"Offers a truly accessible guide to the basics and practice of marketing analytics."--Koen Pauwels, Professor of Marketing at Ozyegin University, Istanbul "and Honorary Professor at the University of Read more...

 
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