Marketing analytics : a practical guide to improving consumer insights using data techniques /

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Bibliographic Details
Author / Creator:Grigsby, Mike, author.
Edition:Second edition.
Imprint:London ; New York, NY : Kogan Page Limited, 2018.
Description:xiv, 217 pages : illustrations ; 24 cm
Language:English
Subject:Marketing research.
Marketing.
Marketing.
Marketing research.
Format: Print Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11738798
Hidden Bibliographic Details
ISBN:9780749482169
0749482168
9780749482176
0749482176
Notes:Includes bibliographical references and index.
Summary:Understand how to apply marketing science techniques fearlessly, to improve consumer insights and compete more effectively in the marketplace.
Other form:Online version: Grigsby, Mike. Marketing analytics. Second edition. London ; New York : Kogan Page, 2018 9780749482176
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245 1 0 |a Marketing analytics :  |b a practical guide to improving consumer insights using data techniques /  |c Mike Grigsby. 
250 |a Second edition. 
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300 |a xiv, 217 pages :  |b illustrations ;  |c 24 cm 
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504 |a Includes bibliographical references and index. 
520 8 |a Understand how to apply marketing science techniques fearlessly, to improve consumer insights and compete more effectively in the marketplace. 
505 0 |a Introduction to marketing analytics -- Part one: Overview-how can marketing analytics help you? -- A brief statistics review -- Brief principles of consumer behaviour and marketing strategy -- What is an insight? -- Part two: Dependent variable techniques -- What drives demand? Modelling dependent variable techniques -- Who is most likely to buy and how do I target them? -- When are my customers most likely to buy? -- Panel regression-how to use a cross-sectional time series -- Systems of equations for modeling dependent varialbe techniques -- Part three: Inter-relationship techniques -- What does my (customer) market look like? Modelling inter-relationship techniques -- Segmentation-tools and techniques -- Part four: More important topics for everyday marketing -- Statistical testing-howdo I know what works? -- Implementing big data and big data analytics -- Part five: Conclusion -- The finale-what should you take away from this? 
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