Building the customer-centric enterprise: data warehousing techniques for supporting customer relationship management
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York [u.a.]
Wiley
2001
|
| Schriftenreihe: | Wiley computer publishing
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XXIV, 487 S. Ill. |
| ISBN: | 0471319813 |
Internformat
MARC
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| 245 | 1 | 0 | |a Building the customer-centric enterprise |b data warehousing techniques for supporting customer relationship management |c Claudia Imhoff ; Lisa Loftis ; Jonathan G. Geiger |
| 246 | 1 | 3 | |a Building the customer centric enterprise |
| 264 | 1 | |a New York [u.a.] |b Wiley |c 2001 | |
| 300 | |a XXIV, 487 S. |b Ill. | ||
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| 650 | 7 | |a Consumentenonderzoek |2 gtt | |
| 650 | 7 | |a Data warehouse |2 gtt | |
| 650 | 7 | |a Dataprocessing |2 gtt | |
| 650 | 7 | |a Relatiemarketing |2 gtt | |
| 650 | 4 | |a Datenverarbeitung | |
| 650 | 4 | |a Customer relations |x Data processing | |
| 650 | 4 | |a Data warehousing | |
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| 700 | 1 | |a Loftis, Lisa |e Verfasser |4 aut | |
| 700 | 1 | |a Geiger, Jonathan G. |e Verfasser |4 aut | |
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Datensatz im Suchindex
| _version_ | 1804128473313181696 |
|---|---|
| adam_text | Acknowledgments Xl
Foreword xi
Introduction xv
Part One Introducing CRM ]
Chapter 1 The Customer Becomes the Center of the Business Universe 3
What Is True Customer Relationship Management? 6
Do We Have True CRM? 7
How Many Customers? °
How Many Products?
How Many Contacts?
The Customer in CRM
The Relationship in CRM j(j
Influence Value in the Contemporary Household i .*
Influence Value in the Extended Household *i
The Management in CRM
Summary: CRM Defined 28
Chapter 2 The Customer and the Corporate Information Factory (C.F) 31
The Need for a Corporate Information Factory Architecture 32
Business Operations ,^
Business Intelligence ^
Business Management
Why the Corporate Information Factory? 37
Til Figure Out What I Want To Do With It.
Data Must Be Specific to My Functional Requirements 42
Data Must Be Reliable and Consistent 46
Data Must Be Delivered in a Timely Manner oO
Data Must Be Easily Accessible , ,.,_ f. t
It Must Be Flexible Enough to Support Multiple Functions oA
It Must Be Detailed Enough to Support All Queries 54
v
An Example of the Corporate Information Factory at Work 56
Execute 57
Monitor 58
Optimize 58
Summary: The Need for Architecture 59
Chapter 3 Understanding the Customer Life Cycle 61
An Overview of the Customer life Cycle 63
The Enterprise, Products, and the Competition 66
Consumers, Prospects, Customers, and You 72
Trust and the Customer Touch Zone 76
Mapping Enterprise Processes to Customer life Cycle Stages 80
Intrude and Engage 80
Acquire 82
Retain and Expand 86
Summary 89
Part Two Planning for CRM 91
Chapter 4 Are You Ready? Tuning the Organization for CRM 93
Critical Success Factors for CRM 95
Implementing a Coordinated, Customer Focused
Business Strategy 96
Creating a CRM Friendly Organization Structure 101
Establishing a CRM Sawy Organization Culture 106
Implementing an Integrated Customer Information
Environment 108
Ensuring Executive Commitment and Support 112
The Marketing, Service, and Sales CRM Roadmap 114
Roadmap for Marketing 115
Roadmap for Customer Service 119
Summary 125
Chapter 5 Getting Underway 127
Program Management 129
Getting Data In versus Getting Information Out 131
Goals of the Getting Data In Team 132
Goals of the Getting Information Out Team 135
Roles and Responsibilities of the Teams 138
Program Management Team 138
Getting Data In Team 146
Getting Information Out Team 151
Summary 155
Chapter 6 Developing an Integrated CRM Technology Environment 157
Overview of the Zachman Framework 158
Zachman Framework Rules 161
Business Model Development Rules 171
Rule 1: Only One Business Model Exists 172
Rule 2: All Business Model Components Must Be Defined 175
Rule 3: An Item May Appear Only Once within the
Business Model 180
Models 182
Function Model 182
Subject Area Model 184
Business Data Model 187
System and Technology Data Model 193
Summary 199
Chapter 7 Capturing Customer Information 201
What Is Data Acquisition? 204
Mapping the Sources to the Targets 207
Creating Sustainable Identifiers 207
Choosing Appropriate Sources 209
Determining Refreshment Frequency 211
Determining Summarized, Derived, and Aggregated Fields 211
Creating the Extraction, Integration, Cleansing, and
Transformation Processes 212
Capturing Data 213
Data Cleansing 220
Integrating Data 221
Transforming the Integrated Data 222
Loading the Data Warehouse or Operational Data Store 223
Loading the Data Warehouse 223
Loading the ODS 226
Creating the Audit and Control Processes 228
Audit and Control Methodology 229
Define Processes and Data Attributes 231
Assess Process and Data Quality 232
Measure Process and Date Quality 232
Correct Errors 233
The Role of Audit and Control Meta Date 234
Meta Data Capture and Maintenance 236
Summary 236
Chapters Quality Relationships Start with Quality Customer Data 239
Quality Defined 240
Myth 1: Quality Means Perfection ^u
Myth 2: Quality Means Luxury 243
Myth 3: Quality Is Expensive 243
Myth 4: Quality Cannot Be Measured 244
Reality Check 245
The Foundations of a Quality Program: Deming s 14 Points 245
Point 1: Create Constancy of Purpose for the Improvement of
Products and Services 247
Point 2: Adopt the New Philosophy 248
Point 3: Cease Dependence on Mass Inspection 249
Point 4: End the Practice of Awarding Business on
Price Tag Alone 251
Point 5: Improve Constantly and Forever the System of
Production and Service 252
Point 6: Institute Training 255
Point 7: Institute Leadership 256
Point 8: Drive Out Fear 257
Point 9: Break Down Barriers between Staff Areas 258
Point 10: Eliminate Slogans, Exhortations, and Targets for the
Workforce 259
Point 11: Eliminate Numerical Quotas 259
Point 12: Remove Barriers to Pride of Workmanship 260
Point 13: Institute a Vigorous Program of Education and
Retraining 261
Point 14: Take Action to Accomplish the Transformation 262
Establishing Quality Customer Data 262
Capturing Data 263
Data Cleansing 266
Integrating Data 268
Transforming Data 269
Loading Data 270
Tools 270
Summary 271
Part Three Implementing CRM 273
Chapter 9 Business Intelligence: Technologies for Understanding
Your Customers 275
Defining the Strategic CRM Components 276
The Data Warehouse 279
Data Marts 281
Departmental versus Application Specific Data Marts 283
Choosing the Best Data Mart Design 287
Determining Alternative Database Designs 290
Data Delivery 295
Decision Support Interface (DSI) 297
Summary 298
Chapter 10 Facilitating Customer Touches with the Customer ODS 303
What Is an ODS? 306
What Is a Customer ODS ... and Why Do I Need One? 309
Overview of an Ideal Customer ODS 313
A Detailed Look at the Ideal Customer ODS 315
Comprehensive Customer Definition 316
Customer Relationships 316
Extensive and Extensible Customer Models 320
Data Quality Tools 322
The Transaction Interface 323
Summary 327
Chapter 11 Automating the Sales and Service Process 329
Why Automate? 331
Automating Customer Service and Sales 333
Automating Service 334
Automating Sales 346
Integrating Sales and Service Applications 353
Summary 358
Chapter 12 Interacting with Customers Online 361
The Impact of E Commerce on CRM 363
E Commerce Models 365
E Commerce Opportunities and Challenges 367
Permission Marketing and Personalization 371
Enabling E Commerce 376
Customer Information for Click Stream Analysis 376
Technology Architecture for E Commerce 381
Summary 386
Chapter 13 Putting It All Together with Enterprise Portals 389
Enterprise Portals Defined 391
Why Enterprise Portals Are Needed 392
Toolbox 395
Library 396
Workbench 398
Developing Enterprise Portals 398
First Generation of Enterprise Portals 399
Second Generation of Enterprise Portals 400
Summary 402
Chapter 14 Preserving Customer Trust The Role of Privacy 405
The Importance of Protecting Privacy 406
Privacy before E Commerce 409
Privacy with E Commerce Engendering Trust 411
Enforcement 412
Privacy Policy Components 414
Information Collected 415
Information Collectors and Users 417
Information Use 418
Customer Choice 419
Ownership 420
Access and Quality Control 420
Security 421
Privacy and the Customer life Cycle 421
Building Trust during Intrude and Engage 422
Building Trust during Acquire 424
Building Trust during Retain and Expand 425
Privacy and the Corporate Information Factory 426
Summary 429
Chapter 15 The Future of CRM 431
The Evolving CRM Definition 433
Successful CRM Organizations of the Future 435
Challenges to CRM Implementation 436
Business Strategy Alignment 436
Loyalty 437
View of the Customer 440
Customer Selection 441
Acquisition Channel 442
Extended Enterprise 443
Commodity Business Environment 444
Organization Structure and Culture 445
Customer Information and Technology 447
Silver Bullet Syndrome 450
Closed Loop Approach 451
Weighing the Costs and Benefits 452
Summary 453
Glossary 457
Recommended Reading 471
Index 473
|
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| indexdate | 2024-07-09T18:49:48Z |
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| language | English |
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| spelling | Imhoff, Claudia Verfasser aut Building the customer-centric enterprise data warehousing techniques for supporting customer relationship management Claudia Imhoff ; Lisa Loftis ; Jonathan G. Geiger Building the customer centric enterprise New York [u.a.] Wiley 2001 XXIV, 487 S. Ill. txt rdacontent n rdamedia nc rdacarrier Wiley computer publishing Consumentenonderzoek gtt Data warehouse gtt Dataprocessing gtt Relatiemarketing gtt Datenverarbeitung Customer relations Data processing Data warehousing Kundenmanagement (DE-588)4236865-0 gnd rswk-swf Data-Warehouse-Konzept (DE-588)4406462-7 gnd rswk-swf Kundenmanagement (DE-588)4236865-0 s Data-Warehouse-Konzept (DE-588)4406462-7 s DE-604 Loftis, Lisa Verfasser aut Geiger, Jonathan G. Verfasser aut HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009334832&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Imhoff, Claudia Loftis, Lisa Geiger, Jonathan G. Building the customer-centric enterprise data warehousing techniques for supporting customer relationship management Consumentenonderzoek gtt Data warehouse gtt Dataprocessing gtt Relatiemarketing gtt Datenverarbeitung Customer relations Data processing Data warehousing Kundenmanagement (DE-588)4236865-0 gnd Data-Warehouse-Konzept (DE-588)4406462-7 gnd |
| subject_GND | (DE-588)4236865-0 (DE-588)4406462-7 |
| title | Building the customer-centric enterprise data warehousing techniques for supporting customer relationship management |
| title_alt | Building the customer centric enterprise |
| title_auth | Building the customer-centric enterprise data warehousing techniques for supporting customer relationship management |
| title_exact_search | Building the customer-centric enterprise data warehousing techniques for supporting customer relationship management |
| title_full | Building the customer-centric enterprise data warehousing techniques for supporting customer relationship management Claudia Imhoff ; Lisa Loftis ; Jonathan G. Geiger |
| title_fullStr | Building the customer-centric enterprise data warehousing techniques for supporting customer relationship management Claudia Imhoff ; Lisa Loftis ; Jonathan G. Geiger |
| title_full_unstemmed | Building the customer-centric enterprise data warehousing techniques for supporting customer relationship management Claudia Imhoff ; Lisa Loftis ; Jonathan G. Geiger |
| title_short | Building the customer-centric enterprise |
| title_sort | building the customer centric enterprise data warehousing techniques for supporting customer relationship management |
| title_sub | data warehousing techniques for supporting customer relationship management |
| topic | Consumentenonderzoek gtt Data warehouse gtt Dataprocessing gtt Relatiemarketing gtt Datenverarbeitung Customer relations Data processing Data warehousing Kundenmanagement (DE-588)4236865-0 gnd Data-Warehouse-Konzept (DE-588)4406462-7 gnd |
| topic_facet | Consumentenonderzoek Data warehouse Dataprocessing Relatiemarketing Datenverarbeitung Customer relations Data processing Data warehousing Kundenmanagement Data-Warehouse-Konzept |
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