Mike Grigsby
Marketing Analytics
Mike Grigsby
Marketing Analytics
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Confidently apply marketing analytics techniques to improve consumer insights and marketing performance, so you can compete more effectively in the marketplace.
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Confidently apply marketing analytics techniques to improve consumer insights and marketing performance, so you can compete more effectively in the marketplace.
Produktdetails
- Produktdetails
- Verlag: Kogan Page Ltd
- 3 Revised edition
- Seitenzahl: 336
- Erscheinungstermin: 3. Dezember 2022
- Englisch
- Abmessung: 234mm x 155mm x 19mm
- Gewicht: 516g
- ISBN-13: 9781398608191
- ISBN-10: 139860819X
- Artikelnr.: 63938765
- Verlag: Kogan Page Ltd
- 3 Revised edition
- Seitenzahl: 336
- Erscheinungstermin: 3. Dezember 2022
- Englisch
- Abmessung: 234mm x 155mm x 19mm
- Gewicht: 516g
- ISBN-13: 9781398608191
- ISBN-10: 139860819X
- Artikelnr.: 63938765
Mike Grigsby, based in Orlando, Florida, has more than 30 years' experience in the field of marketing analytics. He was formerly vice president of customer insights and advanced analytics at Brierley and Partners and of strategic business analysis and advanced analytics at Targetbase and has also held leadership positions at Hewlett-Packard and Gap. Previously an adjunct professor at the University of Texas at Dallas, he taught analytics at both graduate and undergraduate levels. He is the author of Advanced Customer Analytics, also published by Kogan Page.
Section
00: Introduction; Section
PART ONE: How can marketing analytics help you?; Chapter
01: Overview of statistics; Chapter
02: Consumer behaviour and marketing strategy; Chapter
03: What is an insight?; Section
PART TWO: Dependent variable techniques; Chapter
04: Modelling demand and elasticity; Chapter
05: Polynomial distributed lags; Chapter
06: Using Poisson regression; Chapter
07: Logistic regression and market basket analysis; Chapter
08: Survival modelling and lifetime value; Chapter
09: Panel regression and same store sales; Chapter
10: Introduction to forecasting; Section
PART THREE: Interrelationship techniques; Chapter
11: Simultaneous equations; Chapter
12: Principal components and factor analysis; Chapter
13: Segmentation overview; Chapter
14: Tools of segmentation; Section
PART FOUR: Focus on media and loyalty; Chapter
15: Modelling marcom value; Chapter
16: Media mix modelling; Chapter
17: Overview of loyalty; Chapter
18: Loyalty with SEM; Chapter
19: The customer loyalty journey; Section
PART FIVE: More important topics for everyday marketing; Chapter
20: Statistical testing; Chapter
21: Introduction to Big Data; Chapter
22: Conclusion
The finale; Chapter
23: References; Chapter
24: Further reading;
00: Introduction; Section
PART ONE: How can marketing analytics help you?; Chapter
01: Overview of statistics; Chapter
02: Consumer behaviour and marketing strategy; Chapter
03: What is an insight?; Section
PART TWO: Dependent variable techniques; Chapter
04: Modelling demand and elasticity; Chapter
05: Polynomial distributed lags; Chapter
06: Using Poisson regression; Chapter
07: Logistic regression and market basket analysis; Chapter
08: Survival modelling and lifetime value; Chapter
09: Panel regression and same store sales; Chapter
10: Introduction to forecasting; Section
PART THREE: Interrelationship techniques; Chapter
11: Simultaneous equations; Chapter
12: Principal components and factor analysis; Chapter
13: Segmentation overview; Chapter
14: Tools of segmentation; Section
PART FOUR: Focus on media and loyalty; Chapter
15: Modelling marcom value; Chapter
16: Media mix modelling; Chapter
17: Overview of loyalty; Chapter
18: Loyalty with SEM; Chapter
19: The customer loyalty journey; Section
PART FIVE: More important topics for everyday marketing; Chapter
20: Statistical testing; Chapter
21: Introduction to Big Data; Chapter
22: Conclusion
The finale; Chapter
23: References; Chapter
24: Further reading;
Section
00: Introduction; Section
PART ONE: How can marketing analytics help you?; Chapter
01: Overview of statistics; Chapter
02: Consumer behaviour and marketing strategy; Chapter
03: What is an insight?; Section
PART TWO: Dependent variable techniques; Chapter
04: Modelling demand and elasticity; Chapter
05: Polynomial distributed lags; Chapter
06: Using Poisson regression; Chapter
07: Logistic regression and market basket analysis; Chapter
08: Survival modelling and lifetime value; Chapter
09: Panel regression and same store sales; Chapter
10: Introduction to forecasting; Section
PART THREE: Interrelationship techniques; Chapter
11: Simultaneous equations; Chapter
12: Principal components and factor analysis; Chapter
13: Segmentation overview; Chapter
14: Tools of segmentation; Section
PART FOUR: Focus on media and loyalty; Chapter
15: Modelling marcom value; Chapter
16: Media mix modelling; Chapter
17: Overview of loyalty; Chapter
18: Loyalty with SEM; Chapter
19: The customer loyalty journey; Section
PART FIVE: More important topics for everyday marketing; Chapter
20: Statistical testing; Chapter
21: Introduction to Big Data; Chapter
22: Conclusion
The finale; Chapter
23: References; Chapter
24: Further reading;
00: Introduction; Section
PART ONE: How can marketing analytics help you?; Chapter
01: Overview of statistics; Chapter
02: Consumer behaviour and marketing strategy; Chapter
03: What is an insight?; Section
PART TWO: Dependent variable techniques; Chapter
04: Modelling demand and elasticity; Chapter
05: Polynomial distributed lags; Chapter
06: Using Poisson regression; Chapter
07: Logistic regression and market basket analysis; Chapter
08: Survival modelling and lifetime value; Chapter
09: Panel regression and same store sales; Chapter
10: Introduction to forecasting; Section
PART THREE: Interrelationship techniques; Chapter
11: Simultaneous equations; Chapter
12: Principal components and factor analysis; Chapter
13: Segmentation overview; Chapter
14: Tools of segmentation; Section
PART FOUR: Focus on media and loyalty; Chapter
15: Modelling marcom value; Chapter
16: Media mix modelling; Chapter
17: Overview of loyalty; Chapter
18: Loyalty with SEM; Chapter
19: The customer loyalty journey; Section
PART FIVE: More important topics for everyday marketing; Chapter
20: Statistical testing; Chapter
21: Introduction to Big Data; Chapter
22: Conclusion
The finale; Chapter
23: References; Chapter
24: Further reading;