Data-Driven Business Models (with CD-ROM),9780324222333

Data-Driven Business Models (with CD-ROM)

by
Edition: CD
ISBN13: 9780324222333
ISBN10: 0324222335
Format: Hardcover
Pub. Date: 2005-07-28
Publisher(s): Cengage Learning
List Price: $62.95

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Summary

Using measured performance has become a favorite topic of seminars and articles in the trades and business press. This means how you view, develop and run your business - using all of the data available to do that - and how to model and to continuously reinvent that business to meet the needs of current customers and identify and capitalize on new profitable opportunities. Theoretically, every business should be concerned about this subject. But, in general, the idea of business models has become a matter of concern and interest for most companies beyond the level of small business - over $50 or $100 million in annual sales up through the Fortune 100.

Author Biography

Alan Weber is President of Marketing Analytics Group LLC, a provider of database marketing consulting and modeling services

Table of Contents

Preface 13(2)
CHAPTER 1: Business Models: What They Are, How They Work, Why They Are Important 15(22)
Elements of a Business Model
15(2)
Business Modeling and Business Models
17(6)
Fact-Based Decision Making
18(3)
Cross-Silo Cooperation
21(2)
Types of Business Models
23(5)
Four Basic Business Model Structures
23(4)
Autonomous Business Models
27(1)
Business Models in the Environment
28(1)
Creating and Competing with Business Models
29(3)
Understanding the Internal Culture
32(5)
Describing the Unique Value Proposition (UVP)
33(1)
Information Flow Within the Business Model
34(1)
Defining Which Behaviors Can Be Measured
34(3)
CHAPTER 2: Describing the Customers 37(40)
Profiling
43(3)
Mapping as a Profile Tool
46(1)
Profit-Based Segmentation
46(4)
Predictive Modeling
50(2)
Descriptive Modeling
52(7)
Multi-Channel Profiling
57(2)
Overlay Data
59(3)
Survey Data
62(1)
Learning from Our Customers
63(14)
CHAPTER 3: Describing What Customers Do 77(26)
Tracking Behavior
78(1)
Measuring Lift
79(1)
Break-Even(s)
80(5)
Case Study: Variable Break-Even
81(4)
Profitability by Campaign
85(5)
Case Study: Profitability by Campaign
86(4)
Predictive Modeling
90(3)
Advocates, Buyers, and Tryers
93(10)
RFM vs. RFA Analyses
94(1)
Case Study: Recency-Frequency-Average Order (RFA)
95(8)
CHAPTER 4: Quantifying Customer Behavior 103(18)
Lifetime Value
103(10)
Case Study: Lifetime Value
104(9)
Customer Value
113(2)
Customer Value Index
115(6)
Action Based on a Customer Value Index
119(2)
CHAPTER 5: Building Customer Data Files 121(18)
The Progression of an Analysis
122(5)
Merge/Purge Is the Foundation
127(2)
Data Checks
129(1)
Relational Versus Flat Databases
130(1)
Data Format Versus Data Content
131(1)
Different Data Sources Equal Different Data Meanings
132(1)
Realistic Time-Frames
133(3)
Case Study: Business-to-Business Medical Equipment Manufacturer
134(1)
Case Study: Consumer Cataloger
135(1)
Rapid Development Approach
136(3)
CHAPTER 6: Building a Contact Strategy 139(30)
Segmentation Is Tactical; Marketing Is Strategic
140(2)
Segmentation by Frequency of Contact
142(2)
Understanding House File Segmentation
144(15)
Who Should Be Contacted?
145(1)
What Makes Segments Different?
146(4)
What Offers Are Likely to Be Appropriate?
150(1)
Which Customers Are Likely to Be Most Valuable?
151(2)
When Should Contacts Be Made?
153(2)
Where Do Best Customers Come From?
155(2)
Which Media Are Most Effective in Making Contacts?
157(2)
House File Inventory
159(10)
Quantifying the House File Inventory
161(5)
Building Budgets and Sales Projections Using the House File Inventory
166(3)
CHAPTER 7: The Process of Building a Business Model 169(42)
Building a Team
169(10)
Top Management as Director
171(2)
Investors
173(1)
Facilitators
174(2)
Internal Lead Roles
176(1)
Support Roles
177(1)
Employees' Personal and Professional Strengths
178(1)
Business Model Situation Analysis
179(32)
Initial Review
180(2)
Step One: Employ Database Marketing Methodology
182(3)
Step Two: Load Data
185(1)
Step Three: Data Check
186(2)
Step Four: Data Hygiene
188(2)
Step Five: Set Data Dictionary
190(1)
Step Six: Create Reports Describing the Data
191(4)
Step Seven: Data Mining
195(4)
Step Eight: Exploring and Defining Relationships
199(1)
Step Nine: Create Descriptive Statistics
200(2)
Step Ten: Predictive and Descriptive Modeling
202(2)
Step Eleven: Create Final Report Set and Define Update Report Set
204(1)
Step Twelve: Develop and Implement Strategy Based on Findings
204(2)
Step Thirteen: Adjustment Period and Scheduled Updates
206(1)
Step Fourteen: Application Development
207(4)
CHAPTER 8: Changing the Business Model 211(30)
The Pressure for Change
211(8)
Hysteresis
213(1)
Adoption Hurdles
214(1)
Disruptive Technology
215(1)
Disruptive Competition
216(2)
Disruptive Marketplace
218(1)
The Importance of Management Push
219(1)
Obstacles to Change
220(11)
Pressure for Immediate Success
220(1)
Organization Charts Reflect Strategy
221(5)
Managing Rewards and Measurements
226(1)
Agents of Change Versus Agents of Inertia
227(2)
Knowledge of the Business of the Enterprise Is Key
229(2)
Driving Change
231(10)
Organic Growth
231(1)
Partnering
232(1)
Acquisition
233(1)
Creating a Subsidiary
234(1)
Divestment
234(1)
Specialization
235(1)
New Media Channels
236(1)
New Sales Channels
237(1)
New Constituent Relationships
238(1)
Consummating the Sale
239(1)
Pricing
240(1)
CHAPTER 9: Case Studies 241(30)
How Profiling Changed a Business Model
241(4)
How Cluster Analysis Changed a Business Model
245(3)
How Profit-Based Segmentation Changed a Business Model
248(5)
How Predicative Modeling Improved Subscription Marketing Effectiveness
253(18)
Index 271

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