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▼n http://www.overdrive.com |
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▼a 658.8/12
▼2 23 |
| 100 | 1 |
▼a Grigsby, Mike,
▼e author. |
| 245 | 10 |
▼a Advanced customer analytics :
▼b targeting, valuing, segmenting and loyalty techniques /
▼c Mike Grigsby. |
| 263 | |
▼a 1610 |
| 264 | 1 |
▼a London ;
▼a Philadelphia :
▼b Kogan Page,
▼c [2016] |
| 264 | 4 |
▼c 짤2016 |
| 300 | |
▼a 1 online resource. |
| 336 | |
▼a text
▼b txt
▼2 rdacontent |
| 337 | |
▼a computer
▼b n
▼2 rdamedia |
| 338 | |
▼a online resource
▼b nc
▼2 rdacarrier |
| 490 | 1 |
▼a Marketing science series |
| 504 | |
▼a Includes bibliographical references and index. |
| 505 | 0 |
▼a 01 Overview; What is retail?; What is analytics?; Who is this book for?; Why focus on retail?; Why am I making these suggestions?; How is this book organized?; 02 Regression and Factor Analysis; Introduction; Regression 101: What is regression?; Assumptions of classical linear regression; Why is regression important and why is it used?; Factor analysis; Exploratory vs. confirmatory factor analysis; Using factor analysis; Conclusion; 03 Retail; Introduction to retail; Brief history of retail; Retail analytics; Orientation: because retail is ... this book is ... |
| 505 | 8 |
▼a Retail culture and corporate agilityConclusion; 04 Retail; Which CRM systems are used?; Sources of retail data; What is Big Data?; Is it important?; What does it mean for analytics? For strategy?; Why is it important?; Surviving the Big Data panic; Big Data analytics; Conclusion; 05 Understanding and estimating demand; Introduction; Business objective; Using ordinary regression to estimate demand; Properties of estimators; A note on time series data: autocorrelation; Dummy variables; Business case; Conclusion; 06 Price elasticity and discounts; Introduction to elasticity; Modelling elasticity. |
| 505 | 8 |
▼a Business caseConclusion; 07 Valuing marketing communications (marcomm); Business case; Conclusion; 08 Forecasting future demand; Autocorrelation; Dummy variables and seasonality; Business case; Conclusion; 09 Targeting the right customers; Introduction; Business case; Results applied to the model; A brief procedural note; Variable diagnostics; Conclusion; 10 Maximizing the impact of mailing; Introduction; Lift charts; Scoring the database with probability formula; Conclusion; 11 The benefits of product bundling; What is a market basket?; How is it usually done?; Logistic regression. |
| 505 | 8 |
▼a How to estimate/predict the market basketBusiness case; Conclusion; 12 Estimating time of purchase; Introduction; Conceptual overview of survival analysis; More about survival analysis; A procedure suggestion and pseudo-fit; Business case; Model output and interpretation; Conclusion; 13 Investigating the time of product purchase; Competing risks; Conclusion; 14 Increasing customer lifetime value; Descriptive analysis; Predictive analysis; Introduction to tobit analysis; Business case; Conclusion; 15 Modelling counts (transactions); Business case; Conclusion. |
| 505 | 8 |
▼a 16 Quantifying complexity of customer behaviourIntroduction; What are simultaneous equations?; Why go to the trouble to use simultaneous equations?; Business case; A brief note on missing value imputation; Conclusion; 17 Designing effective loyalty programmes; Introduction to loyalty; Is there a range or spectrum of loyalty?; What are the 3Rs of loyalty?; Why design a programme with earn-burn measures?; Business case; Conclusion; 18 Identifying loyal customers; Structural equation modelling (SEM); Business case; Conclusion; 19 Introduction to segmentation; Overview. |
| 520 | |
▼a Expert guidance in a direct and conceptual style on the analytic steps to take to resolve data-heavy retail marketing questions, taking into account consumer behaviour and multi-channel marketing scenarios. |
| 588 | 0 |
▼a Print version record and CIP data provided by publisher; resource not viewed. |
| 590 | |
▼a eBooks on EBSCOhost
▼b All EBSCO eBooks |
| 650 | 0 |
▼a Marketing research. |
| 650 | 0 |
▼a Customer relations. |
| 650 | 0 |
▼a Customer loyalty. |
| 650 | 7 |
▼a BUSINESS & ECONOMICS
▼x Industrial Management.
▼2 bisacsh |
| 650 | 7 |
▼a BUSINESS & ECONOMICS
▼x Management.
▼2 bisacsh |
| 650 | 7 |
▼a BUSINESS & ECONOMICS
▼x Management Science.
▼2 bisacsh |
| 650 | 7 |
▼a BUSINESS & ECONOMICS
▼x Organizational Behavior.
▼2 bisacsh |
| 650 | 7 |
▼a Customer loyalty.
▼2 fast
▼0 (OCoLC)fst00885531 |
| 650 | 7 |
▼a Customer relations.
▼2 fast
▼0 (OCoLC)fst00885533 |
| 650 | 7 |
▼a Marketing research.
▼2 fast
▼0 (OCoLC)fst01010284 |
| 650 | 7 |
▼a Verbraucherforschung
▼2 gnd |
| 650 | 7 |
▼a Kundenbindung
▼2 gnd |
| 650 | 7 |
▼a Marktsegmentierung
▼2 gnd |
| 650 | 7 |
▼a Preisbildung
▼2 gnd |
| 655 | 4 |
▼a Electronic books. |
| 776 | 08 |
▼i Print version:
▼a Grigsby, Mike.
▼t Advanced customer analytics.
▼d London ; New York, NY : Kogan Page, [2016]
▼z 9780749477158
▼w (DLC) 2016033366
▼w (OCoLC)957696196 |
| 830 | 0 |
▼a Marketing science series. |
| 856 | 40 |
▼u http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1365518 |
| 938 | |
▼a ProQuest MyiLibrary Digital eBook Collection
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▼n cis33850258 |
| 938 | |
▼a EBL - Ebook Library
▼b EBLB
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| 938 | |
▼a EBSCOhost
▼b EBSC
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| 938 | |
▼a ProQuest MyiLibrary Digital eBook Collection
▼b IDEB
▼n cis33850258 |
| 938 | |
▼a YBP Library Services
▼b YANK
▼n 13211116 |
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▼a 관리자 |
| 994 | |
▼a 92
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