The new direct marketing: how to implement a profit-driven database marketing strategy
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
New York, NY [u.a.]
McGraw-Hill
1995
|
| Ausgabe: | 2. ed. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIV, 493 S. Ill., graph. Darst. |
| ISBN: | 1556238096 |
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| 250 | |a 2. ed. | ||
| 264 | 1 | |a New York, NY [u.a.] |b McGraw-Hill |c 1995 | |
| 300 | |a XIV, 493 S. |b Ill., graph. Darst. | ||
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| 650 | 4 | |a Datenverarbeitung | |
| 650 | 4 | |a Database management | |
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| 650 | 4 | |a Direct marketing |x Data processing | |
| 650 | 4 | |a Direct marketing |x Statistical methods | |
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Datensatz im Suchindex
| _version_ | 1804124186555187200 |
|---|---|
| adam_text | Contents
Chapter One
AN OVERVIEW OF THE NEW DIRECT MARKETING 1
Introduction, 1
The New Direct Marketing: What Is It?, 3
Applications and Advantages, 5
Lead Grading, 5
Customized Targeting at the Right Time, 5
New Information and Past Results Help Formulate New Strategies, 6
Information Can Drive New Programs and Fuel New Revenue
, Sources, 6
/ Information Can Foster New Services and Generate Repeat Orders, 7
Ongoing Communication Efforts Can Increase Customer Loyalty, 7
Summary, 9
Chapter Two
SOURCES OF MARKETING DATA 10
Transaction Driven Customer and Prospect Data, 10
Customer Performance Data, 10
Prospect Data, 11
Directly Supplied and Externally Acquired Data, 12
Directly Supplied Data, 12
Collecting and Using Directly Supplied Data via Surveys, 14
Data Requested Differ by Industry, 14
Using Survey Data: A Case History, 16
Additional Uses of Survey Results, 17
Using Survey Data to Assign Customers and Prospects
to Segments, 18
Data Purchased from Third Party Sources, 20
Geography Based Demographic Data, 20
National Databases as Sources of Data for File Enhancement, 23
How to Obtain Enhancement Data, 28
National Databases as Sources of Names, 28
Using Acquired Data to Predict Segment Membership, 29
Chapter Three
, BUZZWORDS 30
A Word about Buzzwords, 30
Buzzword 1: Generations of Languages, 30
Procedural Languages, 32
vii
Contents
Buzzword 2: SQL, 32
Buzzword 3: Flat Files and VSAM File Structures, 33
Buzzword 4: Indexes, 34
How Indexes Are Used, 34
Buzzword 5: Productivity Tools, 37
Buzzword 6: Logical and Physical Design, 37
Buzzword 7: CPU, 38
Channel, 38
Channel Contention, 38
Direct Access Storage Device (DASD), 39
Seek Time, 39
Buzzword 8: Summary Files, 39
Normalized, 39
Buzzword 9: Types of Database Products, 40
Hierarchical, 40
Inverted File, 40
Relational, 40
Multiple Specialized Platforms, 40
Chapter Four
t WHY COMPANIES ARE BUILDING DATABASE
MARKETING SYSTEMS 41
Database Marketing Systems, 41
Scope of the Marketing Database Application, 42
The Marketing Database as an Analysis and Promotion Tool Only, 42
Fully Integrated Database System, 43
Other Reasons for Choosing a DBMS Environment, 43
Chapter Five
WHAT DO YOU WANT THE DATABASE TO DO? 44
Key Issues to Consider before Committing to a
Database Strategy, 44
Business Needs and Functional Requirements, 45
Queries, 45
Selecting Names for Future Promotions, 47
Selecting Names Based on Model Scores, 48
Tracking Promotion Results and Profiling, 49
User Friendly Environments, 49
Turnaround Time, 50
Chapter Six
CREATING AND UPDATING THE DATABASE 53
A Framework for Implementing a Database Project, 53
Will the Database Be Created and Maintained In House or at an
Outside Service Bureau?, 54
External Vendors, 54
A Combined Approach, 55
Contents ix
What Data Is Needed to Perform the Required Functions?, 55
Define the Files to Be Included in the Database, 56
Review the Data Elements Contained in Each Contributing File, 56
Select the Data Elements that Are Needed from Each File, 56
Define Data Elements That Must Be Created during Updates, 57
How Will Data Get into the Marketing Database?, 57
In House Processing Implications, 57
Service Bureau Processing Implications, 58
Decide Which, if Any, Data Enhancement Files Will Be Used, 58
Consolidating Records, 59
Duplicate Identification, 59
Address Standardization, 60
Matching Issues, 60
Scrubbing, 61
Householding, 61
Develop a Preliminary Database Design, 63
Frequency of Update or Replacement, 72
Creating Separate Databases for Marketing to Avoid Conflicts, 73
Level of Detail of Data, 74
Will the Database Be Updated or Replaced, 75
Return to Business Needs and Determine Adequacy of Plan for
Meeting Needs, 75
, . Chapter Seven
1/ , HARDWARE AND SOFTWARE ISSUES 77
Developments in Technology, 77
The Impact of Workstations, 78
Hardware Issues, 78
Mainframe Computers, 78
Midframe Computers, 79
Workstations, 80
Microcomputers, 81
Software Issues, 82
Existing Database Management System Software, 82
Types of DMBS Products, 83
Customized Applications for Direct Marketing, 87
Summary, 87
Chapter Eight
IMPACT OF NEW COMPUTER TECHNOLOGY
ON BUSINESS 88
Data Processing Technologies, 88
Computer Applications in Business, 88
Operating Support Systems for Day to Day Processing, 89
Decision Support Systems, 90
Wish List, 91
Contents
Salient Trends in Technology, 91
Improvements in Price Performance, 91
Multiple CPUs, 92
Open Systems Architecture, 93
Standard Interfaces, 93
^Chapter Nine
CONFIGURATIONS TO SUPPORT BUSINESS NEEDS 95
Business Needs and Trends in Computer Technology, 95
Client Server Technology, 95
Benefits of Client Server Configurations, 96
Different Kinds of Clients, 98
Different Kinds of Servers, 98
Different Types of Networks, 99
Examples, 99
Happy Combination of Old and New Technologies, 99
All New Technology, 100
Multilocation Installation Using All New Technology, 101
Revisiting the Wish List and Outlining Future Steps, 101
Chapter Ten
THE BASICS OF STATISTICAL ANALYSIS 103
The Process of Data Analysis, 103
Pictures of Data: Stem and Leaf, 105
Numerical Summaries, 106
Center of Data, 106
Variation within the Data, 107
Confidence Intervals, 109
Theorem 1,110
Theorem 2,114
Confidence Intervals and Tests of Significance for
Response Rates, 114
Theorem 3,114
Tests of Significance—Two Types of Errors and Power, 119
Chapter Eleven
RELATIONSHIPS BETWEEN VARIABLES 121
Correlation Coefficient, 124
Correlation Coefficient for Scalar Variables, 126
Correlation Coefficient in Practice, 128
Simple Regression, 129
The Regression Line, 132
Simple Regression in Practice, 134
Straightening Out the Data, 137
Explanatory Power, 137
Predictive Power, 137
Contents xi
Chapter Twelve
MULTIPLE REGRESSION 140
Multiple Regression Statistics—How to Read Them, 141
Quick and Dirty Regression, 144
More Quick and Dirty Regression, 150
Regression Built with Care, 151
Step 1—Examination of the Correlation Matrix, 151
Step 2—Normalization of All Variables, 152
Step 3—Checking for Linearity, 155
Rerunning the Model, 161
Validation—Choosing the Best Model, 164
Multiple Regression—Some Odds and Ends, 165
Interaction, 165
Multicollinearity, 166
Selection of Variables, 167
Chapter Thirteen
RESPONSE ANALYSIS 169
Introduction, 169
Logistic Regression, 171
Concepts and Definition, 171
Logistic Regression Model, 172
Logistic Equation, 173
Dummy Variables, 174
Logistic Coefficients, 175
Discriminant Analysis, 176
Automatic Interaction Detection—AID/CHAID, 176
The SI CHAID Analysis of the Same Data, 180
Using CHAID in Regression Analysis, 183
Multiple Regression: Guidelines for Building a Model, 186
/ Chapter Fourteen
SEGMENTATION ANALYSIS 187
Data Needed for Segmentation Modeling, 188
Factor Analysis: What It Is and When You Should Use It, 188
How Factor Analysis Works, 190
Running and Interpreting Factor Analysis, 191
Cluster Analysis: What It Is and When You Should Use It, 193
How Cluster Analysis Works, 194
Running and Interpreting Cluster Analysis, 195
Using Small Sample Survey Data to Segment a Much
Bigger File, 196
Concluding Example and Review, 198
Contents
Chapter Fifteen
A CLOSER LOOK BACK 201
A Closer Look at R, the Correlation Coefficient, 201
Review of, 201
Rematching, 202
Rematch Example, 203
Rematching Phi, 204
Implilcation of Rematching, 206
A Closer Look at a Model s Power, 206
An Example, 207
A Closer Look at Straightening Data, 209
Ladder of Powers, 210
Bulging Rule, 211
An Example of the Bulging Rule, 211
A Closer Look at Reexpressions for Many Variables, 216
A Simple PCA Example, 217
Algebraic Properties of PCA, 218
Model Building With PCA—Two Case Studies, 220
1. A Continuity Example, 220
2. A Packaged Goods Example, 222
Chapter Sixteen
ARTIFICIAL NEURAL NETWORKS 224
Introduction, 224
When Are ANN Used, 224
Classification, 224
Prediction, 225
What Are ANNs? 225
Definition, 225
Basic structure, 225
Basic ANN, 226
Basic Architecture, 226
How ANNs Are Trained, 227
Supervised Training Method, 228
Designing an Optimal Multilayer Feedfordward ANN, 229
The Black Box ANN, 299
Proof of the Pudding, 230
ANN Model, 230
Logistic Regression Model, 231
ReRuns, 232
Discussion, 233
Contents xiii
Chapter Seventeen
AN INTRODUCTION TO THE ECONOMICS OF
THE NEW DIRECT MARKETING 235
Implied versus Contractual Relationships, 236
Classical Direct Marketing versus Database Marketing, 237
The Search for the Perfect Control, 238
Once the Customer Is on the File, 238
Some Assumptions about the Economics of Multidivisional
Databases, 240
/^Chapter Eighteen
BACK TO BASICS: THE ECONOMICS OF
CLASSICAL DIRECT MARKETING 241
Solo Promotions, 241
Multistep Promotions Leading to a Direct Sale, 242
Catalog Sales, 243
Continuity Programs, 245
Negative Option clubs, 246
Newsletters, 248
Magazines, 248
Performance Measurement, 249
Front End versus Back End Performance, 249
Front End performance, 249
Measuring Promotion Expense, 249
Calculating CPM for Different Direct Response Media, 250
Measuring Response, 254
One Step Promotions, 254
Two Step Promotions, 254
Calculating Cost per Response, 255
One Step Promotions, 255
Two Step Promotions, 255
Tracking Back End Performance, 256
Measuring Back End Performance, 257
The Return of the Chicken or the Egg Problem, 265
Measuring Profitability: Combining Front End and Back End
Statistics, 266
ROP and the Infamous 2 Percent Response Rate, 270
Contents
Chapter Nineteen
THE ROLE OF MODELING IN THE NEW
DIRECT MARKETING 271
The Difference between Scoring Models and Forecasts, 271
Obtaining Forecasts of Responses, 272
Applying Scoring Models to Forecasts, 273
Response Modeling: RFM versus Regression, 275
The Analyses Compared to RFM Analyses, 277
A Quick Review of Interaction Variables, 277
Trees as a Benchmark against Regression Results, 278
Regression Models, 280
A Reminder about Ordinary versus Logistic Regression Models, 282
Typical Response Model Results, 282
ZIP Code Models, 285
Adjusting for ZIP Code Size, 287
Modeling Variables other than Response, 288
Combining Models—Modeling Profit, 289
A Word of Caution Regarding Combined Models, 291
Lead Conversion Models, 291
Attrition Models, 295
Adding Household Level Overlay Data to Prospect Models, 297
Adding Household Level Overlay Data to Internal Customer
Models, 306
Enhancing Your Database with Internal Survey Data, 309
Implementing Models, 313
Modeling, Managing, and Marketing to Unique Customer
Groups, 312
Chapter Twenty
FINANCIAL MODELS 315
A Financial Model of a New Book Club Business, 316
Lifetime Value, 316
What If , 320
A Catalog Example, 324
Lifetime Value, 324
What If , 326
Conclusion, 327
Appendix A
LOTUS 1 2 3 PROGRAMS 328
Appendix B
VENDORS OF DATA AND COMPUTER SERVICES 337
INDEX 487
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| publisher | McGraw-Hill |
| record_format | marc |
| spelling | The new direct marketing how to implement a profit-driven database marketing strategy David Shepard Associates, Inc. With individual contrib. by Rajeev Batra ... 2. ed. New York, NY [u.a.] McGraw-Hill 1995 XIV, 493 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Datenverarbeitung Database management Database marketing Direct marketing Data processing Direct marketing Statistical methods Database-Marketing (DE-588)4263308-4 gnd rswk-swf Direktmarketing (DE-588)4012421-6 gnd rswk-swf Marketingstrategie (DE-588)4120697-6 gnd rswk-swf Datenbanksystem (DE-588)4113276-2 gnd rswk-swf Statistik (DE-588)4056995-0 gnd rswk-swf Direktmarketing (DE-588)4012421-6 s Datenbanksystem (DE-588)4113276-2 s DE-604 Statistik (DE-588)4056995-0 s 1\p DE-604 Database-Marketing (DE-588)4263308-4 s 2\p DE-604 Marketingstrategie (DE-588)4120697-6 s 3\p DE-604 Batra, Rajeev Sonstige (DE-588)121629791 oth David Shepard Associates Sonstige (DE-588)5145086-0 oth HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=006509003&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | The new direct marketing how to implement a profit-driven database marketing strategy Datenverarbeitung Database management Database marketing Direct marketing Data processing Direct marketing Statistical methods Database-Marketing (DE-588)4263308-4 gnd Direktmarketing (DE-588)4012421-6 gnd Marketingstrategie (DE-588)4120697-6 gnd Datenbanksystem (DE-588)4113276-2 gnd Statistik (DE-588)4056995-0 gnd |
| subject_GND | (DE-588)4263308-4 (DE-588)4012421-6 (DE-588)4120697-6 (DE-588)4113276-2 (DE-588)4056995-0 |
| title | The new direct marketing how to implement a profit-driven database marketing strategy |
| title_auth | The new direct marketing how to implement a profit-driven database marketing strategy |
| title_exact_search | The new direct marketing how to implement a profit-driven database marketing strategy |
| title_full | The new direct marketing how to implement a profit-driven database marketing strategy David Shepard Associates, Inc. With individual contrib. by Rajeev Batra ... |
| title_fullStr | The new direct marketing how to implement a profit-driven database marketing strategy David Shepard Associates, Inc. With individual contrib. by Rajeev Batra ... |
| title_full_unstemmed | The new direct marketing how to implement a profit-driven database marketing strategy David Shepard Associates, Inc. With individual contrib. by Rajeev Batra ... |
| title_short | The new direct marketing |
| title_sort | the new direct marketing how to implement a profit driven database marketing strategy |
| title_sub | how to implement a profit-driven database marketing strategy |
| topic | Datenverarbeitung Database management Database marketing Direct marketing Data processing Direct marketing Statistical methods Database-Marketing (DE-588)4263308-4 gnd Direktmarketing (DE-588)4012421-6 gnd Marketingstrategie (DE-588)4120697-6 gnd Datenbanksystem (DE-588)4113276-2 gnd Statistik (DE-588)4056995-0 gnd |
| topic_facet | Datenverarbeitung Database management Database marketing Direct marketing Data processing Direct marketing Statistical methods Database-Marketing Direktmarketing Marketingstrategie Datenbanksystem Statistik |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=006509003&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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