Grigsby Marketing Analytics
2. Auflage 2018
ISBN: 978-0-7494-8216-9
Verlag: Kogan Page
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Buch, Englisch, Reihe: Marketing Science
240 Seiten, Kartoniert, Format (B × H): 159 mm x 235 mm, Gewicht: 372 g
A Practical Guide to Improving Consumer Insights Using Data Techniques
2. Auflage 2018,
240 Seiten, Kartoniert, Format (B × H): 159 mm x 235 mm, Gewicht: 372 g
Reihe: Marketing Science
ISBN: 978-0-7494-8216-9
Verlag: Kogan Page
Seite exportieren
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- sofort versandfertig, Lieferfrist: 1-3 Werktage
The fully revised second edition of Marketing Analytics includes three new chapters on big data analytics, insights and panel regression, including how to collect, separate and analyze big data. All of the advanced tools and techniques for predictive analytics have been updated, translating models such as tobit analysis for customer lifetime value into everyday use. Whether an experienced practitioner or having no prior knowledge, methodologies are simplified to ensure the more complex aspects of data and analytics are fully accessible for any level of application. Complete with downloadable data sets and test bank resources, this book supplies a concrete foundation to optimize marketing analytics for day-to-day business advantage.
Grigsby, Mike
Mike Grigsby is vice president of customer insights and advanced analytics at Brierley and Partners in Texas, US. With more than 25 years of experience, he is the former vice president of strategic business analysis and advanced analytics at Targetbase, director of marketing science for Millward Brown and has held leadership positions at Hewlett-Packard and Gap. Grigsby is also well-known in academia, having written articles for academic and trade journals. He is a teaching professor for both graduate and undergraduate levels and regularly speaks at trade conventions and seminars.
Introduction to Marketing Analytics;Overview - How Can Marketing Analytics Help You?; A Brief Statistics Review; Brief Principles of Consumer Behaviour and Marketing Strategy; What is an Insight?;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 Modelling Dependent Variable TechniquesInter-Relationship Techniques; What Does My Customer Market Look Like?; Segmentation - Tools and Techniques;More Important Topics for Everyday Marketing; Statistics Testing How Do I Know What Works?; Implementing Big Data and Big Data Analytics;Conclusion; The Finale What Should You Take Away From This?
The fully revised second edition of Marketing Analytics includes three new chapters on big data analytics, insights and panel regression, including how to collect, separate and analyze big data. All of the advanced tools and techniques for predictive analytics have been updated, translating models such as tobit analysis for customer lifetime value into everyday use. Whether an experienced practitioner or having no prior knowledge, methodologies are simplified to ensure the more complex aspects of data and analytics are fully accessible for any level of application. Complete with downloadable data sets and test bank resources, this book supplies a concrete foundation to optimize marketing analytics for day-to-day business advantage.
Grigsby, Mike
Mike Grigsby is vice president of customer insights and advanced analytics at Brierley and Partners in Texas, US. With more than 25 years of experience, he is the former vice president of strategic business analysis and advanced analytics at Targetbase, director of marketing science for Millward Brown and has held leadership positions at Hewlett-Packard and Gap. Grigsby is also well-known in academia, having written articles for academic and trade journals. He is a teaching professor for both graduate and undergraduate levels and regularly speaks at trade conventions and seminars.
Introduction to Marketing Analytics;Overview - How Can Marketing Analytics Help You?; A Brief Statistics Review; Brief Principles of Consumer Behaviour and Marketing Strategy; What is an Insight?;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 Modelling Dependent Variable TechniquesInter-Relationship Techniques; What Does My Customer Market Look Like?; Segmentation - Tools and Techniques;More Important Topics for Everyday Marketing; Statistics Testing How Do I Know What Works?; Implementing Big Data and Big Data Analytics;Conclusion; The Finale What Should You Take Away From This?
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