The new direct marketing : how to implement a profit-driven database marketing strategy

목차 (Table of Contents)

• CONTENTS
• SECTION ONE MARKETING = 1
• Chapter One An Overview of the New Direct Marketing = 2
• Introduction = 2
• The New Direct Marketing - What Is It? = 3
• The Premise of the New Direct Marketing = 4
• An Overview of Some of the Advantages and Practices of the New Direct Marketing = 6
• Lead Grading = 6
• Customized Targeting at the Right Time = 6
• New Information and Past Results Help Formulate Strategies = 7
• Information Can Drive New Programs and Fuel New Revenue Sources = 7
• Information Can Foster New Services and Generate Repeat Orders = 8
• Ongoing Communications Efforts Can Increase Customer Loyalty = 8
• Summary = 9
• Chapter Two Contact Strategy = 11
• Introduction = 11
• Contact Strategy - What Is It? = 11
• RFM : The Workhorse Variables of Both the New and the Old Direct Marketing = 12
• Using Purchase History Information to Develop Contact Strategies = 12
• Using Promotion History to Define Contact Eligibility and Propensity to Respond = 14
• Using Demographic Data to Create Actionable Market Segments for the Purpose of Contact Strategy = 15
• Combining Both Purchase History and Demographic Data Can Lead to New Opportunities = 15
• Using Attitudinal Data to Create Actionable Market Segments for the Purpose of Contact Strategy = 16
• Specific Examples of the Role of Contact Strategy = 17
• Summary = 23
• Marketing Pmgram Strategy Guideline Checklist = 23
• Chapter Three Buzzwords = 29
• A Word about Buzzwords = 29
• Buzzword 1 : Generation of Languages = 29
• Procedural Languages = 30
• Buzzword 2 : SQL = 31
• Buzzword 3 : Flat Files and VSAM File Structures = 31
• Buzzword 4 : Indexes = 32
• How Indexes Are Used = 32
• Buzzword 5 : Productivity Tools = 35
• Buzzword 6 : Logical and Physical Design = 36
• Buzzword 7 : CPU = 36
• Channel = 37
• Channel Contention = 37
• Direct Access Storage Device(DASD) = 37
• Seek Time = 37
• Buzzword 8 : Summary Files = 38
• Normalization = 38
• Buzzword 9 : Types of Database Products = 38
• Hierarchical = 38
• Inverted File = 38
• Relational = 38
• Proprietaiy Database Systems = 39
• Other Database-Related Topics = 39
• Buzzword 10 : Internet Buzzwords = 40
• Chapter Four Sources and Uses of Marketing Data = 42
• Customer and Prospect Data = 42
• Customer Data = 42
• Prospect Data = 44
• Nontransactional Data Sources = 46
• Examples of the Type of Data Collected from Three Types of Direct Marketing Business = 49
• Financial Services Marketers = 49
• Examples of Questions Asked by Financial Services Marketers = 49
• Negative Options and Continuity Marketers = 50
• Examples of Questions Asked by Book and Music Clubs = 50
• Insurance Marketers = 51
• Using Questionnaires to Gather Data = 52
• Using Survey Data to Assign Customers and Prospects to Segments = 52
• Data Purchased from Third-Party Sources = 54
• National Databases as Sources of Data for File Enhancement = 57
• National Databases as Sources of Names = 62
• Using Acquired Data to Predict Segment Membership = 63
• Chapter Five Relationship Marketing and How It Relates to the New Direct Marketing = 64
• Some Background and Attempts at Definitions = 64
• Mass Markets = 64
• Today's Markets - The Impact of Technology = 65
• Today's Markets - The Impact of Demographic Trends = 65
• Relationship Marketing＝Customer Retention + Share of Customer = 66
• Developing Relationship Marketing Capabilities = 66
• Customer Information = 67
• Customization and Added Value = 69
• Two-Way Communication and Increased "Bandwidth" = 70
• Relationship Marketing and Marketing Objectives = 73
• Chapter Six The Role of Direct Marketing in Building Brands = 75
• Conventional Wisdom = 75
• What Does It Mean to Build Brand Equity? = 75
• Building Awareness through Direct Marketing = 76
• Building a Quality Reputation through Direct Marketing = 77
• Communicating Quality = 77
• Building Other Associations through Direct Marketing = 78
• Building Loyalty through Direct Marketing = 78
• Conclusions and Summary = 79
• Chapter Seven Customer Service and Direct Marketing = 80
• Required Customer Services Capabilities = 81
• Information Needed by Customer Service = 83
• Marketing Information Can Be Collected by Customer Service = 84
• Capturing Survey Data = 86
• Marketing Information to Be Provided to Customer Service = 88
• Customer Service and the Internet = 89
• SECTION TWO DATA AND MARKETING DATABASES = 93
• Chapter Eight What Do You Want Your Database to Do and Why Do You Think It Will Do It? = 94
• Introduction = 94
• Key Issues to Consider before Starting a Marketing Database Project = 94
• One Size Does Not Fit All = 94
• Cost-Justifying the Investment in a Marketing Database = 95
• How a Marketing Database Will Affect the Organization = 96
• Data : Learning to Live with Impeifect Data = 96
• Managing Expectations-Everybody's Expectations = 97
• Objectives, Processes, and Requirements = 97
• Marketing Tools = 99
• Business Needs and Functional Requirements = 100
• User-Friendly Environments = 105
• Turnaround Times = 106
• Chapter Nine Building a Marketing Database = 107
• A Framework for Implementing a Database Project = 107
• Will the Database Be Created and Maintained In-House or at an Outside Service Bureau? = 108
• Cost = 108
• Control = 109
• Customization = 109
• External Vendors = 110
• A Combined Approach = 111
• What Data Is Needed to Perform the Required Functions? = 112
• Identify the Files to Be Included in the Database = 112
• Review the Data Elements Contained in Each Contributing File = 113
• Select the Data Elements That Are Needed from Each File = 113
• Define Data Elements That Must Be Created during the Update Process = 113
• How Will Data Get into the Marketing Database? = 113
• In-House Processing Implications = 114
• Service Bureau Processing Implications = 115
• Decide Which, If Any, Data Enhancements Files Will Be Used = 115
• Consolidating Records = 115
• Duplicate Identification = 116
• Address Standardization = 117
• Matching Issues = 117
• Scrubbing = 117
• Householding = 118
• Develop a Preliminary Database Design = 120
• Frequency of Update or Replacement = 120
• Creating Separate Databases for Marketing to Avoid Conflict = 121
• Levels of Detail of Data = 131
• Will the Database Be Updated or Replaced? = 131
• Return to the Business Needs and Determine the Adequacy of the Plan for Meeting Those Needs = 132
• Chapter Ten Using Data Hygiene to Identify Individuals and Households = 134
• Real-World Issues = 134
• Data Hygiene = 135
• Other Benefits of Data Hygiene = 137
• Applying Hygiene = 137
• Name Standardization = 137
• Address Standardization = 138
• Postal Address Standards = 138
• File Scrubbing = 140
• Determining Deliverability = 140
• Comparison among Files = 141
• Duplicate identification = 141
• Householding = 142
• Other Uses for Duplicate Information = 142
• Merge／Purge Techniques and Software = 143
• Using Address Hygiene for Marketing Databases = 144
• The Consolidation Process = 144
• Establishing More Complex Relationships = 146
• Chapter Eleven Campaign Management = 147
• Campaign Phases = 147
• Management Processes = 148
• The Campaign Planning Phase = 149
• The Campaign Development Phase = 150
• The Campaign Execution Phase = 152
• The Campaign Analysis Phase = 152
• Profile Analysis = 153
• Response Analysis = 153
• Campaign Content and Structure Data = 154
• Actuals Data = 155
• Conclusion = 155
• SECTION THREE WHAT DIRECT MARKETERS NEED TO KNOW ABOUT TECHNOLOGY = 157
• Chapter Twelve Operations and Decision Support Systems = 158
• A Very Brief History of Computer Applications in Business = 158
• Operating Support Systems for Day-to-Day Processing = 159
• Decision Support Applications Can Be a Drain on Mainframe Resources = 160
• Decision Support Systems = 160
• Need for Flexibility and Quick Response = 160
• DSS Technology = 160
• Integrating Operations Support Systems and Decision Support Systems = 161
• Chapter Thirteen The Unique Requirements Direct Marketers Place on Their Decision Support System = 162
• Direct Marketing's Functional Requirements = 162
• Chapter Fourteen Hardware and Software Fundamentals = 164
• Hardware = 164
• Mainframes = 164
• Midframes = 165
• Workstations = 166
• Microcomputers = 167
• All Database Management Systems Require a Great Deal of Computer Capacity = 168
• Software = 168
• File structures = 168
• Chapter Fifteen Trends in Technology = 178
• Improvements in Price Performance = 178
• Multiple CPUs = 179
• Open Systems Architecture = 179
• Standard Interfaces = 180
• Evolution of Relational DBMSs = 181
• Salient Characteristics of Relational DBMSs = 181
• Capabilities and Performance of SQL = 182
• Post-SQL Processing for Direct Marketing = 184
• The Performance Dilemma = 184
• Solutions to the Database Performance Problem = 184
• Data Warehouses and Data Marts = 185
• Enterprise Data Warehouses = 185
• Data Marts = 187
• OLAP／EIS = 187
• On-Line Analytical Processing = 188
• Executive Information System = 188
• The Marketing Operations System = 190
• Chapter Sixteen Client Server Systems = 195
• Client-Server Technology = 195
• Benefits of Client-Server Configurations = 197
• Different Kinds of Clients = 198
• Different Kinds of Servers = 198
• Different Types of Networks = 199
• Examples = 199
• Happy Combination of Old and New Technologies = 200
• All New Technology = 200
• Multilocation Installation Using All New Technology = 201
• Revisiting the Wish List and Outlining Future Steps = 201
• SECTION FOUR BASIC STATISTICS AND MODELING = 203
• Chapter Seventeen The Basics of Statistical Analysis = 204
• The Process of Data Analysis = 204
• Pictures of Data : Stem and Leaf = 206
• Numerical Summaries = 207
• Center of Data = 208
• Variation within the Data = 209
• Confidence Intervals = 210
• Theorem1 = 212
• Theorem 2 = 215
• Confidence Intervals and Tests of Significance for Response Rates = 215
• Theorem 3 = 215
• Tests of Significance - Two Types of Errors and Power = 219
• Chapter Eighteen Relationships between Variables = 222
• Correlation Coefficient = 225
• Correlation Coefficient for Scalar Variables = 227
• Correlation Coefficient in Practice = 228
• Simple Regression = 233
• The Regression Line = 233
• Simple Regression in Practice = 235
• Straightening Out the Data = 238
• Explanatory Power = 239
• Predictive Power = 239
• Chapter Nineteen Multiple Regression = 241
• Multiple Regression Statistics -How to Read Them = 242
• Quick and Dirty Regression = 245
• More Quick and Dirty Regression = 251
• Regression Built with Care = 253
• Step 1 Examination of the Correlation Matrix = 253
• Step 2 Normalization of All Variables = 253
• Step 3 Checking for Linearity = 254
• Rerunning the Model = 262
• Validation - Choosing the Best Model = 264
• Multiple Regression-Some Odds and Ends = 266
• Interaction = 266
• Multicollinearity = 267
• Selection of Variables = 268
• Chapter Twenty Response Analysis = 270
• Introduction = 270
• Logistic Regression = 272
• Concepts and Definition = 272
• Logistic Regression Model = 274
• Logistic Equation = 274
• Summary Variables = 274
• Logistic Coefficients = 276
• Discriminant Analysis = 277
• Automatic Interaction Detection - AID／CHAID = 277
• The SI-CHAID Analysis of the Same Data = 281
• Using CHALD in Regression Analysis = 284
• Multiple Regression : Guidelines for Building a Model = 287
• Chapter Twenty-one Segmentation Analysis = 288
• Data Needed for Segmentation Modeling = 289
• Factor Analysis : What It Is and When You Should Use It = 289
• How Factor Analysis Works = 290
• Running and Interpreting Factor Analysis = 292
• Cluster Analysis : What It Is and When You Should Use It = 293
• How Cluster Analysis Works = 295
• Running and Interpreting Cluster Analysis = 295
• Using Small-Sample Survey Data to Segment a Much Bigger File = 297
• Concluding Example and Review = 298
• Chapter Twenty-two A Closer Look Back = 302
• A Closer Look at r, the Correlation Coefficient = 302
• Review of r = 302
• Rematching = 303
• Rematch Example = 304
• Rematching Phi = 305
• Implication of Rematching = 307
• A Closer Look at a Model's Power = 308
• An Example = 308
• A Closer Look at Straightening Data = 311
• Ladder of Powers = 312
• Bulging Rule = 312
• An Example of the Bulging Rule = 313
• A Closer Look at Reexpressions for Many Variables = 318
• A Simple PCA Example = 318
• Algebraic Properties of PCA = 320
• Model Building with PCA - Two Case Studies = 322
• A Continuity Example = 322
• A Packaged Goods Example = 324
• Chapter Twenty-three Artificial Neural Networks = 326
• Introduction = 326
• When Are ANNs Used = 326
• Classfication = 327
• Prediction = 327
• What Are ANNs? = 327
• Definition = 327
• Basic Structure = 328
• Basic ANN = 328
• Basic Architecture = 329
• How ANNs Are Trained = 330
• Supervised Training Method = 331
• Designing an Optimal Multilayer Feedforward ANN = 331
• The Black Box ANN = 332
• Proof of the Pudding = 333
• ANN Model = 333
• Logistic Regression Model = 334
• Reruns = 334
• Discussion = 336
• SECTION FIVE ADVANCED MODELING = 339
• Chapter Twenty-four Assessment of Direct Marketing Response Models = 340
• Accuracy = 340
• Decile Analysis = 341
• Precision = 342
• Separability = 344
• All Together Now(Discussion) = 344
• Chapter Twenty-five Direct Marketing Models Using Genetic Algorithms = 345
• What Is Optimization? = 345
• What Is a Genetic Algorithm? = 346
• Illustration of a Simple GA = 346
• Reproduction = 347
• Crossover = 348
• Mutation = 350
• GAs Today = 351
• GAs : Strengths and Limitations = 351
• The Genetic Algorithm DMAX Model = 352
• DMAX Fitness Function = 352
• DMAX Response Model = 352
• Powerful Response Modeling = 3S3
• DMAX Discrete Profit Model = 353
• DMAX Regression = 355
• DMAX Improvement over Ordinaty Regression = 357
• DMAX Guarantee = 358
• Chapter Twenty-six Bootstrapping in Direct Marketing = 359
• Traditional Response Model Validation = 359
• Illustration = 359
• Three Questions = 360
• The Bootstrap = 361
• How to Bootstrap = 362
• Simple Illustration = 363
• Bootstrap Performance = 364
• Bootstrap Decile Analysis Validation = 364
• One More Question = 365
• Bootstrap Computation = 366
• Summary = 366
• Chapter Twenty-seven What Do My Customers Look Like? Look at the Stars! = 367
• Star Graph Basics = 367
• Illustration = 368
• Star Graphs for Single Variables = 368
• Star Graphs for Many Variables Considered Jointly = 369
• Conclusion = 370
• Chapter Twenty-eight Alternative Direct Marketing Response Models : Linear Probability, Logit and Probit Models = 371
• Linear Probability Model = 371
• Logit and Probit Models = 372
• Illustration = 373
• Discussion of Table 28-5 = 373
• Conclusion = 376
• Chapter Twenty-nine CHAID for Interpreting a Logistic Regression Model = 379
• Logistic Regression Model = 379
• Direct Marketing Response Model(Real Study) = 379
• CHAID = 380
• CHAID Trees = 382
• CHAID Tree Graphs = 384
• Summary = 388
• Chapter Thirty Market Classification Modeling with Logistic Regression = 390
• Binary Logistic Regression = 390
• Some Notation = 391
• Polychotomous Logistic Regression = 391
• Model Building with PLR = 392
• Market Segmentation Classification Model = 392
• Survey of Cellular Phone Users = 392
• Data = 393
• CHAID Analysis = 393
• CHAID Tree Graphs = 396
• Market Segment Classification Model = 399
• Summary = 401
• Chapter Thirty-one Modern Methods of Testing in Direct Marketing = 402
• Introduction = 402
• Common Direct Marketing Testing Rules = 402
• Test One Thing at a Time = 402
• Test ALL Things = 403
• Statistical Experimental Design = 404
• Designed Experiments = 404
• Experimental Designs = 404
• Analyses of Experimental Designs = 405
• Blocking = 405
• Efficiency of Experimental Designs = 407
• Multifactor Experiments = 408
• Factorial Experiments = 408
• Statistical Experimental Design Rules = 411
• SECTION SIX ECONOMICS, LIFETIME VALUE, AND THE ROLE OF MODELING IN THE NEW DIRECT MARKETING = 413
• Chapter Thirty-two An Introduction to the Economics of the New Direct Marketing = 414
• Implied versus Contractual Relationships = 415
• Classical Direct Marketing versus Database Marketing = 416
• The Search for the Perfect Control = 417
• Once the Customer Is on the File = 417
• Some Assumptions about the Economics of Multidivisional Databases = 419
• Chapter Thrity-three Back to Basics : The Economics of Classical Direct Marketing = 420
• Solo Promotions = 421
• Multystep Promotions Leading to a Sale = 421
• Catalog Sales = 422
• Continuity Sales = 424
• Negative Option Clubs = 425
• Newsletters = 426
• Magazines = 427
• Performance Measurement = 427
• Front-End versus Back-End Peiformance = 427
• Calculating CPM for Different Direct Response Media = 428
• Measuring Response = 433
• One-Step Promotions = 433
• Two-Step Promotions = 433
• Calculating Cost per Response = 434
• One-Step Promotions = 434
• Tracking Back-End Performance = 435
• Measuring Back-End Peiformance = 436
• Attributing and Measuring Lifetime Value in a Financial Services Environment = 444
• The Return of the Chicken-or-the-Egg Problem = 446
• Measuring Profitability : Combining Front-End and Back-End Measurements = 446
• ROP and the Infamous 2 Percent Response Rate = 450
• Appendix to Chapter 33 The Present Value Concept = 451
• Chapter Thirty-four The Role of Modeling in the New Direct Marketing = 477
• The Difference between Scoring Models and Forecasts = 478
• Obtaining Forecasts of Response = 479
• Applying Scoring Models to Forecasts = 479
• implementing Scoring Models at the Individual Level = 481
• Response Modeling : RFM versus Regression = 482
• Eliminating Arbitraty Decisions fivm RFM = 483
• Tree Analyses Compared with RFM Analyses = 484
• A Quick Review of interaction Variables = 484
• Trees as a Benchmark against Regression = 485
• CHAID, the Great Equalizer = 487
• Using Principal Components to Model Product Usage Patterns = 488
• Regression Models = 490
• Reminder about Ordinary versus Logistic Regression Models = 492
• How to Determine the Right Number of Variables to include in Your Model = 492
• Typical Response Model Results = 493
• ZIP Code Models = 495
• Adjusting for ZIP Code Size = 498
• Modeling Variables Other Than Response = 498
• Combining Models Modeling Profit = 500
• A Word of Caution : Regarding Combined Models = 502
• Lead-Conversion Models = 503
• Attrition Models = 506
• Adding Household-Level Overlay Data to Prospect Models = 507
• Adding Household-Level Overlay Data to Internal Customer Models = 516
• Enhancing Your Database with Internal Survey Data = 519
• Implementing Models = 523
• Modeling, Managing, and Marketing to Unique Customer Segments = 523
• Chapter Thirty-five Applications of the New Direct Marketing = 526
• About This Chapter = 526
• Moving from the Old to the New Direct Marketing = 526
• General Applications of the New Direct Marketing = 528
• Respond to Events = 529
• Create Market Segments - One Customer at a Time = 529
• Predict Customer／Prospect Behavior = 531
• Create, Test, and Evaluate Marketing Strategies = 531
• Specific Direct Marketing Applications = 532
• Marketing to Current Customers = 532
• New-Customer Acquisition = 547
• Chapter Thirty-six Financial Models = 550
• Negative Option Clubs = 552
• Calculating Lifetime Value = 552
• "What if" scenarios = 561
• Building Catalog Models = 563
• Calculating Lifetime Value = 564
• Appendixes = 569
• Appendix A LOTUS 1-2-3 Programs = 570
• Appendix B Vendors of Data = 579
• Appendix C Fast-Count™ DBMS = 697
• INDEX = 705