| 000 -LEADER |
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| fixed length control field |
07407cam a2200361 a 4500 |
| FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
150427s2015 enka 000 0 eng |
| LIBRARY OF CONGRESS CONTROL NUMBER |
|---|
| LC control number |
2015016002 |
| INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9780749474171 |
| INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| Cancelled/invalid ISBN |
9780749474188 (ebk) |
| CATALOGING SOURCE |
|---|
| Original cataloging agency |
DLC |
| Language of cataloging |
eng |
| Transcribing agency |
DLC |
| AUTHENTICATION CODE |
|---|
| Authentication code |
pcc |
| LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
HF5415.2 |
| Item number |
.G754 2015 |
| DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
658.8/3 |
| Edition number |
23 |
| OTHER CLASSIFICATION NUMBER |
|---|
| Classification number |
BUS043060 |
| -- |
COM021030 |
| -- |
BUS090010 |
| Source of number |
bisacsh |
| SYSTEM CONTROL NUMBER |
|---|
| System control number |
(IMchF)fol15664869 |
| DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20170126100952.0 |
| CONTROL NUMBER |
|---|
| control field |
62776 |
| CONTROL NUMBER IDENTIFIER |
|---|
| control field |
UOWD |
| MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Grigsby, Mike |
| TITLE STATEMENT |
|---|
| Title |
Marketing analytics : |
| Remainder of title |
a practical guide to real marketing science |
| Statement of responsibility, etc |
Mike Grigsby |
| PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc |
London : |
| Name of publisher, distributor, etc |
Kogan Page, |
| Date of publication, distribution, etc |
c2015. |
| PHYSICAL DESCRIPTION |
|---|
| Extent |
xv, 232 p. : |
| Other physical details |
ill. ; |
| Dimensions |
24 cm. |
| SERIES STATEMENT |
|---|
| Series statement |
Marketing science series |
| SUMMARY, ETC. |
|---|
| Summary, etc |
"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 through a series of problems by providing various data modeling options as solutions. By using this format of presenting a problem and multiple ways to solve it, this book both makes marketing science accessible to beginners and aids the more experienced practitioner in understanding the more complex aspects of data analytics to refine their skills and compete more effectively in the workplace"-- |
| -- |
Provided by publisher. |
| GENERAL NOTE |
|---|
| General note |
"Marketing Analytics arms business analysts and marketers with the marketing science understanding and techniques they need to solve real-world marketing problems, from pulling a targeted list and segmenting data to testing campaign effectiveness and forecasting demand. Assuming no prior knowledge, this book outlines everything practitioners need to 'do' marketing science and demonstrate value to their organization. It introduces concepts relating to statistics, marketing strategy and consumer behaviour and then works through a series of marketing problems in a straightforward, jargon-free way. It demonstrates solutions for various data modelling scenarios and includes full workings and critical analyses to reinforce the key concepts. By starting with the marketing problem and then sharing a series of data modelling options on how to solve it, Marketing Analytics both makes marketing science accessible for beginners and aids the more seasoned practitioner in getting to grips with the trickier technical aspects of data analytics to refine their marketing skills and toolkit and compete more effectively in the marketplace. About the series: The Marketing Science series makes difficult topics accessible to marketing students and practitioners by grounding them in business reality. Each book is written by an expert in the field and includes case studies and illustrations so marketers can gain confidence in applying the tools and techniques and commission external research"-- |
| FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Machine generated contents note: Foreword -- PrefaceIntroduction Part One: Overview01 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 modelling can maximize revenue in a retail/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 to use simultaneous equations? -- Desirable properties of estimators -- Business case -- Checklist: You'll be the smartest person in the room if you...Part Three Inter-relationship techniques 07 Modelling inter-relationship techniques: what does my (customer) market look like? -- 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 RFM? -- Abstract -- What is RFM? -- What is behavioural segmentation? -- What does behavioural segmentation provide that RFM does not? -- Conclusion -- Sidebar: 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: how do I know what works? -- Everyone wants to test -- Sample size equation: use the lift m. |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Marketing research |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Marketing |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
BUSINESS & ECONOMICS |
| Form subdivision |
Marketing |
| -- |
Research |
| Source of heading or term |
bisacsh |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
COMPUTERS |
| Form subdivision |
Database Management |
| -- |
Data Mining |
| Source of heading or term |
bisacsh |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
BUSINESS & ECONOMICS |
| Form subdivision |
E-Commerce |
| -- |
Internet Marketing |
| Source of heading or term |
bisacsh |
| ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
REGULAR |