Verfügbarkeit: Database marketing | Technische Universität München

Database marketing: analyzing and managing customers

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Bibliographische Detailangaben
Beteiligte Personen:	Blattberg, Robert C. 1942- (VerfasserIn), Kim, Pyǒng-do 1958- (VerfasserIn), Neslin, Scott A. 1952- (VerfasserIn)
Format:	Buch
Sprache:	Englisch
Veröffentlicht:	New York, NY Springer 2008
Schriftenreihe:	International series in quantitative marketing
Schlagwörter:	Consumer profiling Database marketing Direktmarketing Database-Marketing Datenbank
Links:	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015748193&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
Beschreibung:	Literaturangaben S. 801 - 845
Umfang:	XXIV, 871 S. zahlr. graph. Darst. 229 mm x 152 mm
ISBN:	0387725784 9780387725789 9781441903327

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Datensatz im Suchindex

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adam_text	Contents Preface ....................................................... vii Part I Strategic Issues 1 Introduction .............................................. 3 1.1 What Is Database Marketing? ............................ 3 1.1.1 Defining Database Marketing ...................... 4 1.1.2 Database Marketing, Direct Marketing, and Customer Relationship Management ......................... 5 1.2 Why Is Database Marketing Becoming More Important? .... 6 1.3 The Database Marketing Process ......................... 8 1.4 Organization of the Book ................................ 12 2 Why Database Marketing? ............................... 13 2.1 Enhancing Marketing Productivity ....................... 13 2.1.1 The Basic Argument .............................. 13 2.1.2 The Marketing Productivity Argument in Depth ..... 15 2.1.3 Evidence for the Marketing Productivity Argument ... 19 2.1.4 Assessment ...................................... 22 2.2 Creating and Enhancing Customer Relationships ........... 23 2.2.1 The Basic Argument .............................. 23 2.2.2 Customer Relationships and the Role of Database Marketing ....................................... 23 2.2.3 Evidence for the Argument that Database Marketing Enhances Customer Relationships .................. 28 2.2.4 Assessment ...................................... 31 2.3 Creating Sustainable Competitive Advantage .............. 32 2.3.1 The Basic Argument .............................. 32 2.3.2 Evolution of the Sustainable Competitive Advantage Argument ....................................... 32 2.3.3 Assessment ...................................... 44 2.4 Summary .............................................. 45 Organizing for Database Marketing ....................... 47 3.1 The Customer-Centric Organization ...................... 47 3.2 Database Marketing Strategy ............................ 48 3.2.1 Strategies for Implementing DBM .................. 49 3.2.2 Generating a Competitive Advantage ............... 51 3.2.3 Summary ........................................ 51 3.3 Customer Management: The Structural Foundation of the Customer-Centric Organization .......................... 52 3.3.1 What Is Customer Management? ................... 52 3.3.2 The Motivation for Customer Management .......... 53 3.3.3 Forming Customer Portfolios ...................... 54 3.3.4 Is Customer Management the Wave of the Future? ... 55 3.3.5 Acquisition and Retention Departmentalization ...... 56 3.4 Processes for Managing Information: Knowledge Management 57 3.4.1 The Concept ..................................... 57 3.4.2 Does Effective Knowledge Management Enhance Performance? .................................... 58 3.4.3 Creating Knowledge .............................. 59 3.4.4 Codifying Knowledge ............................. 60 3.4.5 Transferring Knowledge ........................... 61 3.4.6 Using Knowledge ................................. 62 3.4.7 Designing a Knowledge Management System ......... 63 3.4.8 Issues and Challenges ............................. 65 3.5 Compensation and Incentives ............................ 65 3.5.1 Theory .......................................... 66 3.5.2 Empirical Findings ............................... 67 3.5.3 Summary ........................................ 69 3.6 People ................................................ 69 3.6.1 Providing Appropriate Support .................... 69 3.6.2 Intra-Firm Coordination .......................... 70 Customer Privacy and Database Marketing ............... 75 4.1 Background ............................................ 75 4.1.1 Customer Privacy Concerns and Their Consequences for Database Marketers ........................... 75 4.1.2 Historical Perspective ............................. 78 4.2 Customer Attitudes Toward Privacy ...................... 79 4.2.1 Segmentation Schemes ............................ 79 4.2.2 Impact of Attitudes on Database Marketing Behaviors 81 4.2.3 International Differences in Privacy Concerns ........ 82 4.3 Current Practices Regarding Privacy ...................... 85 4.3.1 Privacy Policies .................................. 85 4.3.2 Collecting Data .................................. 87 4.3.3 The Legal Environment ........................... 88 4.4 Potential Solutions to Privacy Concerns ................... 91 4.4.1 Software Solutions ................................ 91 4.4.2 Regulation ...................................... 91 4.4.3 Permission Marketing ............................. 94 4.4.4 Customer Data Ownership ........................ 96 4.4.5 Focus on Trust ................................... 97 4.4.6 Top Management Support ......................... 98 4.4.7 Privacy as Profit Maximization .................... 99 4.5 Summary and Avenues for Research ...................... 100 Part II Customer Lifetime Value (LTV) 5 Customer Lifetime Value: Fundamentals ..................105 5.1 Introduction ...........................................105 5.1.1 Definition of Lifetime Value of a Customer ..........106 5.1.2 A Simple Example of Calculating Customer Lifetime Value ..........................106 5.2 Mathematical Formulation of LTV ........................108 5.3 The Two Primary LTV Models: Simple Retention and Migration ................................109 5.3.1 Simple Retention Models ..........................109 5.3.2 Migration Models ................................114 5.4 LTV Models that Include Unobserved Customer Attrition .....................................121 5.5 Estimating Revenues ....................................130 5.5.1 Constant Revenue per Period Model ................130 5.5.2 Trend Models ....................................130 5.5.3 Causal Models ...................................130 5.5.4 Stochastic Models of Purchase Rates and Volume .....131 6 Issues in Computing Customer Lifetime Value ............133 6.1 Introduction ...........................................133 6.2 Discount Rate and Time Horizon ......................... 134 6.2.1 Opportunity Cost of Capital Approach ..............134 6.2.2 Discount Rate Based on the Source-of-Risk Approach ..........................140 6.3 Customer Portfolio Management .........................142 6.4 Cost Accounting Issues ..................................145 6.4.1 Activity-Based Costing (ABC) .....................145 6.4.2 Variable Costs and Allocating Fixed Overhead .......148 6.5 Incorporating Marketing Response ........................154 6.6 Incorporating Externalities ..............................158 Customer Lifetime Value Applications ....................161 7.1 Using LTV to Target Customer Acquisition ................161 7.2 Using LTV to Guide Customer Reactivation Strategies ......163 7.3 Using SMC s Model to Value Customers ...................164 7.4 A Case Example of Applying LTV Modeling ...............168 7.5 Segmentation Methods Using Variants of LTV .............172 7.5.1 Customer Pyramids ..............................172 7.5.2 Creating Customer Portfolios Using LTV Measures . .. 174 7.6 Drivers of the Components of LTV .......................175 7.7 Forcasting Potential LTV ................................176 7.8 Valuing a Firm s Customer Base .........................178 Part III Database Marketing Tools: The Basics 8 Sources of Data ...........................................183 8.1 Introduction ...........................................183 8.2 Types of Data for Describing Customers ...................184 8.2.1 Customer Identification Data ...................... 184 8.2.2 Demographic Data ............................... 186 8.2.3 Psychographic or Lifestyle Data .................... 186 8.2.4 Transaction Data ................................. 188 8.2.5 Marketing Action Data ........................... 190 8.2.6 Other Types of Data .............................. 191 8.3 Sources of Customer Information ......................... 191 8.3.1 Internal (Secondary) Data .........................192 8.3.2 External (Secondary) Data ........................193 8.3.3 Primary Data ....................................211 8.4 The Destination Marketing Company .....................213 9 Test Design and Analysis .................................215 9.1 The Importance of Testing ...............................215 9.2 To Test or Not to Test ..................................216 9.2.1 Value of Information ..............................216 9.2.2 Assessing Mistargeting Costs ......................221 9.3 Sampling Techniques ....................................223 9.3.1 Probability Versus Nonprobability Sampling .........224 9.3.2 Simple Random Sampling .........................224 9.3.3 Systematic Random Sampling ......................225 9.3.4 Other Sampling Techniques ........................226 9.4 Determining the Sample Size .............................227 9.4.1 Statistical Approach ..............................227 9.4.2 Decision Theoretic Approach ......................229 9.5 Test Designs ...........................................235 9.5.1 Single Factor Experiments .........................235 9.5.2 Multifactor Experiments: Full Factorials .............238 9.5.3 Multifactor Experiments: Orthogonal Designs ........241 9.5.4 Quasi-Experiments ...............................243 10 The Predictive Modeling Process .........................245 10.1 Predictive Modelling and the Quest for Marketing Productivity .................................245 10.2 The Predictive Modeling Process: Overview ................248 10.3 The Process in Detail ...................................248 10.3.1 Define the Problem ...............................248 10.3.2 Prepare the Data .................................250 10.3.3 Estimate the Model ...............................256 10.3.4 Evaluate the Model ...............................259 10.3.5 Select Customers to Target ........................267 10.4 A Predictive Modeling Example ..........................275 10.5 Long-Term Considerations ...............................280 10.5.1 Preaching to the Choir ............................280 10.5.2 Model Shelf Life and Selectivity Bias ...............280 10.5.3 Learning from the Interpretation of Predictive Models ................................284 10.5.4 Predictive Modeling Is a Process to Be Managed ...................................285 10.6 Future Research ........................................286 Part IV Database Marketing Tools: Statistical Techniques 11 Statistical Issues in Predictive Modeling ..................291 11.1 Economic Justification for Building a Statistical Model ......292 11.2 Selection of Variables and Models ........................293 11.2.1 Variable Selection ................................293 11.2.2 Variable Transformations ..........................299 11.3 Treatment of Missing Variables ...........................301 11.3.1 Casewise Deletion ................................302 11.3.2 Pairwise Deletion .................................302 11.3.3 Single Imputation ................................302 11.3.4 Multiple Imputation ..............................303 11.3.5 Data Fusion .....................................305 11.3.6 Missing Variable Dummies ........................307 11.4 Evaluation of Statistical Models ..........................308 11.4.1 Dividing the Sample into the Calibration and Validation Sample ................................309 11.4.2 Evaluation Criteria ...............................312 11.5 Concluding Note: Evolutionary Model-Building .............321 12 RFM Analysis ............................................323 12.1 Introduction ...........................................323 12.2 The Basics of the RFM Model ...........................324 12.2.1 Definition of Recency, Frequency, and Monetary Value ..................................324 12.2.2 RFM for Segment-Level Prediction .................326 12.3 Breakeven Analysis: Determining the Cutoff Point ..........327 12.3.1 Profit Maximizing Cutoff Response Probability .......328 12.3.2 Heterogeneous Order Amounts .....................329 12.4 Extending the RFM Model ..............................331 12.4.1 Treating the RFM Model as ANOVA ...............331 12.4.2 Alternative Response Models Without Discretization. . 334 12.4.3 A Stochastic RFM Model by Colombo and Jiang (1999).....................................336 13 Market Basket Analysis ..................................339 13.1 Introduction ...........................................339 13.2 Benefits for Marketers ...................................340 13.3 Deriving Market Basket Association Rules .................341 13.3.1 Setup of a Market Basket Problem .................341 13.3.2 Deriving Interesting Association Rules ............342 13.3.3 Zhang (2000) Measures of Association and Dissociation .................................345 13.4 Issues in Market Basket Analysis .........................346 13.4.1 Using Taxonomies to Overcome the Dimensionality Problem .........................................346 13.4.2 Association Rules for More than Two Items .........347 13.4.3 Adding Virtual Items to Enrich the Quality of the Market Basket Analysis ...........................348 13.4.4 Adding Temporal Component to the Market Basket Analysis .........................................349 13.5 Conclusion ............................................350 14 Collaborative Filtering ....................................353 14.1 Introduction ...........................................353 14.2 Memory-Based Methods .................................354 14.2.1 Computing Similarity Between Users ................356 14.2.2 Evaluation Metrics ...............................360 14.3 Model-Based Methods ..................................363 14.3.1 The Cluster Model ...............................364 14.3.2 Item-Based Collaborative Filtering .................364 14.3.3 A Bayesian Mixture Model by Chien and George (1999)..........................366 14.3.4 A Hierarchical Bayesian Approach by Ansari et al. (2000) ..........................................366 14.4 Current Issues in Collaborative Filtering ..................368 14.4.1 Combining Content-Based Information Filtering with Collaborative Filtering ............................368 14.4.2 Implicit Ratings ..................................372 14.4.3 Selection Bias ....................................374 14.4.4 Recommendations Across Categories ................375 15 Discrete Dependent Variables and Duration Models ......377 15.1 Binary Response Model .................................378 15.1.1 Linear Probability Model .......................... 378 15.1.2 Binary Logit (or Logistic Regression) and Probit Models .......................................... 379 15.1.3 Logistic Regression with Rare Events Data .......... 382 15.1.4 Discriminant Analysis ............................. 385 15.2 Multinomial Response Model ............................ 386 15.3 Models for Count Data .................................. 388 15.3.1 Poisson Regression ............................... 388 15.3.2 Negative Binomial Regression ...................... 389 15.4 Censored Regression (Tobit) Models and Extensions ........ 390 15.5 Time Duration (Hazard) Models .......................... 392 15.5.1 Characteristics of Duration Data ...................393 15.5.2 Analysis of Duration Data Using a Classical Linear Regression .......................................394 15.5.3 Hazard Models ...................................395 15.5.4 Incorporating Covariates into the Hazard Function ... 398 16 Cluster Analysis ..........................................401 16.1 Introduction ...........................................401 16.2 The Clustering Process ..................................402 16.2.1 Selecting Clustering Variables ...................... 403 16.2.2 Similarity Measures ............................... 404 16.2.3 Clustering Methods ............................... 408 16.2.4 The Number of Clusters ........................... 418 16.3 Applying Cluster Analysis ............................... 419 16.3.1 Interpreting the Results ...........................419 16.3.2 Targeting the Desired Cluster ......................420 17 Decision Trees ............................................423 17.1 Introduction ...........................................423 17.2 Fundamentals of Decision Trees ..........................424 17.3 Finding the Best Splitting Rule ..........................427 17.3.1 Gini Index of Diversity ............................427 17.3.2 Entropy and Information Theoretic Measures ........429 17.3.3 Chi-Square Test ..................................430 17.3.4 Other Splitting Rules .............................432 17.4 Finding the Right Sized Tree .............................432 17.4.1 Pruning .........................................432 17.4.2 Other Methods for Finding the Right Sized Tree .....434 17.5 Other Issues in Decision Trees ............................435 17.5.1 Multivariate Splits ................................436 17.5.2 Cost Considerations ..............................436 17.5.3 Finding an Optimal Tree ..........................436 17.6 Application to a Direct Mail Offer ........................437 17.7 Strengths and Weaknesses of Decision Trees ...............438 18 Artificial Neural Networks ................................443 18.1 Introduction ...........................................443 18.1.1 Historical Remarks ...............................443 18.1.2 ANN Applications in Database Marketing ...........444 18.1.3 Strengths and Weaknesses .........................445 18.2 Models of Neurons ......................................447 18.3 Multilayer Perceptrons ..................................450 18.3.1 Network Architecture .............................451 18.3.2 Back-Propagation Algorithm .......................454 18.3.3 Application to Credit Scoring ......................455 18.3.4 Optimal Number of Units in the Hidden Layer, Learning-Rate, and Momentum Parameters ..........457 18.3.5 Stopping Criteria .................................457 18.3.6 Feature (Input Variable) Selection ..................458 18.3.7 Assessing the Importance of the Input Variables ......459 18.4 Radial-Basis Function Networks ..........................460 18.4.1 Background .....................................460 18.4.2 A Curve-Fitting (Approximation) Problem ..........461 18.4.3 Application Example .............................463 19 Machine Learning ........................................465 19.1 Introduction ...........................................465 19.2 1-Rule ................................................466 19.3 Rule Induction by Covering Algorithms ...................468 19.3.1 Covering Algorithms and Decision Trees .............469 19.3.2 PRISM .........................................470 19.3.3 A Probability Measure for Rule Evaluation and the INDUCT Algorithm .......................474 19.4 Instance-Based Learning ................................477 19.4.1 Strengths and Limitations .........................478 19.4.2 A Brief Description of an Instance-Based Learning Algorithm .......................................478 19.4.3 Selection of Exemplars ............................479 19.4.4 Attribute Weights ................................481 19.5 Genetic Algorithms .....................................481 19.6 Bayesian Networks .....................................484 19.7 Support Vector Machines ................................486 19.8 Combining Multiple Models: Committee Machines ..........489 19.8.1 Bagging .........................................490 19.8.2 Boosting ........................................491 19.8.3 Other Committee Machines ........................492 Part V Customer Management 20 Acquiring Customers ..................................... 495 20.1 Introduction ........................................... 495 20.2 The Fundamental Equation of Customer Equity ............ 496 20.3 Acquisition Costs ....................................... 497 20.4 Strategies for Increasing Number of Customers Acquired .................................... 499 20.4.1 Increasing Market Size ............................ 499 20.4.2 Increasing Marketing Acquisition Expenditures ....... 500 20.4.3 Changing the Shape of the Acquisition Curve ........ 501 20.4.4 Using Lead Products ............................. 503 20.4.5 Acquisition Pricing and Promotions ................ 504 20.5 Developing a Customer Acquisition Program ............... 505 20.5.1 Framework ...................................... 505 20.5.2 Segmentation, Targeting and Positioning (STP) ...... 506 20.5.3 Product/Service Offering .......................... 507 20.5.4 Acquisition Targeting ............................. 508 20.5.5 Targeting Methods for Customer Acquisition ......... 510 20.6 Research Issues in Acquisition Marketing .................. 514 21 Cross-Selling and Up-Selling .............................. 515 21.1 The Strategy .......................................... 515 21.2 Cross-Selling Models .................................... 516 21.2.1 Next-Product-to-Buy Models ...................... 517 21.2.2 Next-Product-to-Buy Models with Explicit Consideration of Purchase Timing .................. 529 21.2.3 Next-Product-to-Buy with Timing and Response ..... 534 21.3 Up-Selling ............................................. 537 21.3.1 A Data Envelope Analysis Model ................... 538 21.3.2 A Stochastic Frontier Model ....................... 540 21.4 Developing an Ongoing Cross-Selling Effort ................ 541 21.4.1 Process Overview ................................. 541 21.4.2 Strategy ......................................... 541 21.4.3 Data Collection .................................. 544 21.4.4 Analytics ........................................ 544 21.4.5 Implementation .................................. 546 21.4.6 Evaluation ......................................546 21.5 Research Needs ........................................ 547 22 Frequency Reward Programs .............................549 22.1 Definition and Motivation ...............................549 22.2 How Frequency Reward Programs Influence Customer Behavior ..............................................550 22.2.1 Mechanisms for Increasing Sales ....................550 22.2.2 What We Know About How Customers Respond to Reward Programs ................................552 22.3 Do Frequency Reward Programs Increase Profits in a Competitive Environment? ..............................562 22.4 Frequency Reward Program Design .......................565 22.4.1 Design Decisions .................................565 22.4.2 Infrastructure ....................................565 22.4.3 Enrollment Procedures ............................566 22.4.4 Reward Schedule .................................566 22.4.5 The Reward .....................................569 22.4.6 Personalized Marketing ...........................571 22.4.7 Partnering .......................................572 22.4.8 Monitor and Evaluate .............................573 22.5 Frequency Reward Program Examples ....................573 22.5.1 Harrah s Entertainment1 ..........................573 22.5.2 The UK Supermarket Industry: Nectar Versus Clubcard .................................574 22.5.3 Cingular Rollover Minutes .........................576 22.5.4 Hilton Hotels ....................................576 22.6 Research Needs ........................................578 23 Customer Tier Programs .................................579 23.1 Definition and Motivation ...............................579 23.2 Designing Customer Tier Programs .......................581 23.2.1 Overview ........................................581 23.2.2 Review Objectives ................................582 23.2.3 Create the Customer Database .....................582 23.2.4 Define Tiers .....................................582 23.2.5 Determine Acquisition Potential for Each Tier .......584 23.2.6 Determine Development Potential for Each Tier ......585 23.2.7 Allocate Funds to Tiers ...........................588 23.2.8 Design Tier-Specific Programs .....................595 23.2.9 Implement and Evaluate ..........................596 23.3 Examples of Customer Tier Programs .....................597 23.3.1 Bank One (Hartfeil 1996)..........................597 23.3.2 Royal Bank of Canada (Rasmusson 1999)............598 23.3.3 Thomas Cook Travel (Rasmusson 1999).............598 23.3.4 Canadian Grocery Store Chain (Grant and Schlesinger 1995).................................598 23.3.5 Major US Bank (Rust et al. 2000)..................599 23.3.6 Viking Office Products (Miller 2001)................600 23.3.7 Swedbank (Storbacka and Luukinen 1994, see also Storbacka 1993)..................................600 23.4 Risks in Implementing Customer Tier Programs ............601 23.5 Future Research Requirements ...........................604 24 Churn Management ......................................607 24.1 The Problem ...........................................607 24.2 Factors that Cause Churn ...............................611 24.3 Predicting Customer Churn ..............................615 24.3.1 Single Future Period Models .......................616 24.3.2 Time Series Models ...............................622 24.4 Managerial Approaches to Reducing Churn ................625 24.4.1 Overview ........................................625 24.4.2 A Framework for Proactive Churn Management ......627 24.4.3 Implementing a Proactive Churn Management Program ............................631 24.5 Future Research ........................................633 25 Multichannel Customer Management .....................635 25.1 The Emergence of Multichannel Customer Management ..................................636 25.1.1 The Push Toward Multichannel ....................636 25.1.2 The Pull of Multichannel ..........................636 25.2 The Multichannel Customer .............................637 25.2.1 A Framework for Studying the Customer s Channel Choice Decision ..................................637 25.2.2 Characteristics of Multichannel Customers ...........638 25.2.3 Determinants of Channel Choice ...................641 25.2.4 Models of Customer Channel Migration .............647 25.2.5 Research Shopping ...............................652 25.2.6 Channel Usage and Customer Loyalty ...............655 25.2.7 The Impact of Acquisition Channel on Customer Behavior ............................655 25.2.8 The Impact of Channel Introduction on Firm Performance .............................657 25.3 Developing Multichannel Strategies .......................659 25.3.1 Framework for the Multichannel Design Process ......659 25.3.2 Analyze Customers ...............................659 25.3.3 Design Channels .................................661 25.3.4 Implementation ..................................667 25.3.5 Evaluation ......................................668 25.4 Industry Examples .....................................672 25.4.1 Retail Best Practice (Crawford 2002) .............672 25.4.2 Waters Corporation (CRM ROI Review 2003)........672 25.4.3 The Pharmaceutical Industry (Boehm 2002).........673 25.4.4 Circuit City (Smith 2006; Wolf 2006) ...............674 25.4.5 Summary ........................................674 26 Acquisition and Retention Management ..................675 26.1 Introduction ...........................................675 26.2 Modeling Acquisition and Retention ......................676 26.2.1 The Blattberg and Deighton (1996) Model ...........676 26.2.2 Cohort Models ...................................682 26.2.3 Type II Tobit Models .............................682 26.2.4 Competitive Models ..............................687 26.2.5 Summary: Lessons on How to Model Acquisition and Retention .......................................689 26.3 Optimal Acquisition and Retention Spending ..............690 26.3.1 Optimizing the Blattberg/Deighton Model with No Budget Constraint ................................691 26.3.2 The Relationship Among Acquisition and Retention Costs, LTV, and Optimal Spending: If Acquisition Costs Exceed Retention Costs , Should the Firm Focus on Retention? ..............................695 26.3.3 Optimizing the Budget-Constrained Blattberg/Deighton Model .........................698 26.3.4 Optimizing a Multi-Period, Budget-Constrained Cohort Model ....................................702 26.3.5 Optimizing the Reinartz et al. (2005) Tobit Model .....................................705 26.3.6 Summary: When Should We Spend More on Acquisition or Retention? .........................706 26.4 Acquisition and Retention Budget Planning ................708 26.4.1 The Customer Management Marketing Budget (CMMB) ........................................708 26.4.2 Implementation Issues ............................709 26.5 Acquisition and Retention Strategy: An Overall Framework .. 710 Part VI Managing the Marketing Mix 27 Designing Database Marketing Communications ..........715 27.1 The Planning Process ...................................715 27.2 Setting the Overall Plan .................................716 27.2.1 Objectives .......................................716 27.2.2 Strategy .........................................717 27.2.3 Budget.......................................... 717 27.2.4 Summary ........................................ 718 27.3 Developing Copy ....................................... 719 27.3.1 Creative Strategy ................................ 719 27.3.2 The Offer ....................................... 723 27.3.3 The Product ..................................... 726 27.3.4 Personalizing Multiple Components of the Communication .................................. 736 27.4 Selecting Media ........................................ 737 27.4.1 Optimization .................................... 737 27.4.2 Integrated Marketing Communications .............. 739 27.5 Evaluating Communications Programs .................... 739 28 Multiple Campaign Management .........................743 28.1 Overview ..............................................743 28.2 Dynamic Response Phenomena ...........................744 28.2.1 Wear-in, Wear-out, and Forgetting ..................744 28.2.2 Overlap .........................................749 28.2.3 Purchase Acceleration, Loyalty, and Price Sensitivity Effects .......................750 28.2.4 Including Wear-in, Wear-out, Forgetting, Overlap, Acceleration, and Loyalty .........................752 28.3 Optimal Contact Models ................................753 28.3.1 A Promotions Model (Ching et al 2004) ............755 28.3.2 Using a Decision Tree Response Model (Simester et al. 2006).............................756 28.3.3 Using a Hazard Response Model (Gönül et al. 2000) ...............................758 28.3.4 Using a Hierarchical Bayes Model (Rust and Verhoef 2005)...........................................760 28.3.5 Incorporating Customer and Firm Dynamic Rationality (Gönül and Shi 1998)...................763 28.3.6 Incorporating Inventory Management (Bitran and Mondschein 1996)................................765 28.3.7 Incorporating a Variety of Catalogs (Campbell et al. 2001) ............................768 28.3.8 Multiple Catalog Mailings (Eisner et al. 2003, 2004).................................772 28.3.9 Increasing Response to Online Panel Surveys (Neslin et al. 2007)........................774 28.4 Summary ..............................................777 29 Pricing ...................................................781 29.1 Overview - Customer-based Pricing .......................781 xxiv Contents 29.2 Customer Pricing when Customers Can Purchase Multiple One-Time Products from the Firm ........................783 29.2.1 Case 1: Only Product 1 Is Purchased ...............786 29.2.2 Case 2: Two Product Purchase Model with Lead Product 1.......................................786 29.3 Pricing the Same Products/Services to Customers over Two Periods .......................................788 29.3.1 Pessimistic Case: R < q - Expectations of Quality are Less than Actual Quality ......................789 29.3.2 Optimistic Case: R > q - Expectations of Quality are Greater than Actual Quality ............790 29.3.3 Research Issues ..................................790 29.4 Acquisition and Retention Pricing Using the Customer Equity Model ..........................................791 29.5 Pricing to Recapture Customers ..........................794 29.6 Pricing Add-on Sales ....................................796 29.7 Price Discrimination Through Database Targeting Models ... 797 References ....................................................801 Author Index .................................................847 Subject Index ................................................859
any_adam_object	1
author	Blattberg, Robert C. 1942- Kim, Pyǒng-do 1958- Neslin, Scott A. 1952-
author_GND	(DE-588)170875407 (DE-588)174000189 (DE-588)170191397
author_facet	Blattberg, Robert C. 1942- Kim, Pyǒng-do 1958- Neslin, Scott A. 1952-
author_role	aut aut aut
author_sort	Blattberg, Robert C. 1942-
author_variant	r c b rc rcb p d k pdk s a n sa san
building	Verbundindex
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callnumber-first	H - Social Science
callnumber-label	HF5415
callnumber-raw	HF5415.126
callnumber-search	HF5415.126
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callnumber-subject	HF - Commerce
classification_rvk	QP 621 QP 650
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dewey-full	658.8/72
dewey-hundreds	600 - Technology (Applied sciences)
dewey-ones	658 - General management
dewey-raw	658.8/72
dewey-search	658.8/72
dewey-sort	3658.8 272
dewey-tens	650 - Management and auxiliary services
discipline	Informatik Wirtschaftswissenschaften
format	Book
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illustrated	Illustrated
indexdate	2024-12-20T12:57:40Z
institution	BVB
isbn	0387725784 9780387725789 9781441903327
language	English
oai_aleph_id	oai:aleph.bib-bvb.de:BVB01-015748193
oclc_num	212409900
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owner	DE-N2 DE-703 DE-1049 DE-92 DE-739 DE-945 DE-573 DE-91 DE-BY-TUM DE-1050 DE-355 DE-BY-UBR DE-384 DE-19 DE-BY-UBM
owner_facet	DE-N2 DE-703 DE-1049 DE-92 DE-739 DE-945 DE-573 DE-91 DE-BY-TUM DE-1050 DE-355 DE-BY-UBR DE-384 DE-19 DE-BY-UBM
physical	XXIV, 871 S. zahlr. graph. Darst. 229 mm x 152 mm
publishDate	2008
publishDateSearch	2008
publishDateSort	2008
publisher	Springer
record_format	marc
series2	International series in quantitative marketing
spellingShingle	Blattberg, Robert C. 1942- Kim, Pyǒng-do 1958- Neslin, Scott A. 1952- Database marketing analyzing and managing customers Consumer profiling Database marketing Direktmarketing (DE-588)4012421-6 gnd Database-Marketing (DE-588)4263308-4 gnd Datenbank (DE-588)4011119-2 gnd
subject_GND	(DE-588)4012421-6 (DE-588)4263308-4 (DE-588)4011119-2
title	Database marketing analyzing and managing customers
title_auth	Database marketing analyzing and managing customers
title_exact_search	Database marketing analyzing and managing customers
title_full	Database marketing analyzing and managing customers Robert C. Blattberg ; Byung-Do Kim ; Scott A. Neslin
title_fullStr	Database marketing analyzing and managing customers Robert C. Blattberg ; Byung-Do Kim ; Scott A. Neslin
title_full_unstemmed	Database marketing analyzing and managing customers Robert C. Blattberg ; Byung-Do Kim ; Scott A. Neslin
title_short	Database marketing
title_sort	database marketing analyzing and managing customers
title_sub	analyzing and managing customers
topic	Consumer profiling Database marketing Direktmarketing (DE-588)4012421-6 gnd Database-Marketing (DE-588)4263308-4 gnd Datenbank (DE-588)4011119-2 gnd
topic_facet	Consumer profiling Database marketing Direktmarketing Database-Marketing Datenbank
url	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015748193&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
work_keys_str_mv	AT blattbergrobertc databasemarketinganalyzingandmanagingcustomers AT kimpyongdo databasemarketinganalyzingandmanagingcustomers AT neslinscotta databasemarketinganalyzingandmanagingcustomers

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