Marketing Engineering: Computer-Assisted Marketing Analysis and Planning

by ;
Edition: 2nd
Format: Hardcover
Pub. Date: 2002-03-01
Publisher(s): Pearson College Div
List Price: $124.00

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Summary

Turning conceptual marketers into marketing engineers. June 2004 update: This title is now available solely through the authors. Students may purchase it online at http://www.trafford.com/4dcgi/view-item?item=5338 Please make a note of this change since Prentice Hall will not be reprinting this title or able to offer it once our current inventory is depleted. Marketing professionals today are surrounded by information technology, which they need to exploit to succeed in their markets. This is a major change from the days when conceptual skills alone might have been sufficient to be a successful marketer. Today's marketers need to go beyond conceptual marketing and embrace marketing engineering, using data, information technologies, and computer decision models to make marketing decisions. In the new edition of this text, the authors integrate concepts, analytic marketing techniques, and a software toolkit to train the new generation of marketers to become successful marketing engineers.

Table of Contents

Preface xvii
About the Authors xxiii
PART I The Basics 1(60)
Introduction
1(28)
Marketing Engineering: From Mental Models to Decision Models
1(5)
Marketing and marketing management
1(1)
Marketing engineering
2(3)
Why marketing engineering?
5(1)
Marketing Decision Models
6(7)
Definition
6(1)
Characteristics of decision models
7(1)
Verbal, graphical, and mathematical models
8(3)
Descriptive and normative decision models
11(2)
Benefits of Using Decision Models
13(6)
Philosophy and Structure of the Book
19(4)
Philosophy
19(2)
Objectives and structure of the book
21(1)
Design criteria for the software
22(1)
Overview of the Software
23(2)
Software access options
23(1)
Running marketing engineering
24(1)
Summary
25(3)
How Many Draft Commercials Exercise
28(1)
Tools for Marketing Engineering: Market Response Models
29(32)
Why Response Models?
29(2)
Types of Response Models
31(2)
Some Simple Market Response Models
33(4)
Calibration
37(2)
Objectives
39(3)
Multiple Marketing-Mix Elements: Interactions
42(1)
Dynamic Effects
42(2)
Market-Share Models and Competitive Effects
44(2)
Response at the Individual Customer Level
46(4)
Shared Experience and Qualitative Models
50(2)
Choosing, Evaluating, and Benefiting From a Marketing Response Model
52(1)
Summary
53(1)
Appendix: About Excel's Solver
54(2)
How Solver Works
56(2)
Conglomerate, Inc. Promotional Analysis
58(2)
Conglomerate, Inc. Response Model Exercise
60(1)
PART II Developing Market Strategies 61(172)
Segmentation and Targeting
61(56)
The Segmentation Process
61(14)
Defining segmentation
61(1)
Segmentation theory and practice
62(2)
The STP approach
64(2)
Segmenting markets (Phase 1)
66(2)
Describing market segments (Phase 2)
68(1)
Evaluating segment attractiveness (Phase 3)
69(1)
Selecting target segments and allocating resources to segments (Phase 4)
70(3)
Finding targeted customers (Phase 5)
73(2)
Defining a Market
75(3)
Segmentation Research: Designing and Collecting Data
78(5)
Developing the measurement instrument
78(1)
Selecting the sample
79(1)
Selecting and aggregating respondents
79(4)
Segmentation Methods
83(13)
Using factor analysis to reduce the data
84(1)
Forming segments by cluster analysis: Measures of association
84(4)
Clustering methods
88(4)
Interpreting segmentation study results
92(4)
Behavior-Based Segmentation: Cross-Classification, Regression, and Choice Models
96(5)
Cross-classification analysis
96(1)
Regression analysis
96(1)
Choice-based segmentation
97(4)
Customer Heterogeneity in Choice Models
101(1)
Implementing the STP Process
102(1)
Summary
103(1)
Conglomerate Inc.'s New PDA (2001)
104(1)
Introducting the Connector
104(1)
The History of the PDA
105(1)
PDA Types
105(1)
The PDA Customer
106(1)
PDA Features
106(1)
Facts About the PDA Market
106(1)
The HVC Survey
107(1)
The Questionnaire
107(3)
Questions for determining segmentation-basis or needs variables
107(1)
Questions for determining variables for discriminant analysis
108(2)
Appendix: PDA Features Guide
110(3)
Operating system
110(1)
Screen
110(1)
Memory
110(1)
Ergonomics
111(1)
Synchronization
111(1)
Batteries
111(1)
Modem & online services
111(1)
Web
111(1)
Email, etc.
111(1)
Handwriting recognition
111(1)
Other software
112(1)
Accessories
112(1)
Audio
112(1)
ABB Electric Segmentation Case
113(1)
History
113(1)
Situation in 1974
113(1)
New Strategy at ABB Electric
113(1)
Establishing the MKIS Program
114(1)
Choice Modeling
115(1)
Postscript: Situation in 1988
116(1)
Positioning
117(38)
Differentiation and Positioning
117(2)
Definition
117(1)
Positioning Strategy
118(1)
Positioning Using Perceptual Maps
119(3)
Applications of Perceptual Maps
122(6)
Perceptual Mapping Techniques
128(11)
Attribute-based methods
128(8)
Similarity-based methods for perceptual mapping
136(3)
Joint-Space Maps
139(6)
Overview
139(1)
Simple joint-space maps
139(2)
External analysis using PREFMAP3
141(4)
Incorporating Price in Perceptual Maps
145(1)
Summary
146(1)
Appendix: Factor Analysis for Preprocessing Segmentation Data
147(1)
Positioning the Infiniti G20 Case
148(1)
Introducing the G20
148(1)
Background
148(1)
Research Data
148(7)
Strategic Market Analysis: Conceptual Framework and Tools
155(33)
Strategic Marketing Decision Making
155(4)
Market Demand and Trend Analysis
159(16)
Judgmental methods
160(1)
Market and product analysis
161(1)
Time-series methods
162(5)
Causal methods
167(7)
What method to choose?
174(1)
The Product Life Cycle
175(5)
Cost Dynamics: Scale and Experience Effects
180(3)
Summary
183(2)
Bookbinders Book Club Case
185(1)
The Bookbinders Book Club
185(3)
Models for Strategic Marketing Decision Making
188(45)
Market Entry and Exit Decisions
188(10)
Shared Experience Models: The PIMS Approach
198(3)
Product Portfolio Models
201(7)
The Boston Consulting Group (BCG) approach
201(2)
The GE/McKinsey approach
203(1)
Financial models
204(1)
Analytic Hierarchy Process
205(3)
Competition
208(4)
Summary
212(1)
ICI Americas R&D Project Selection Case
213(3)
Product Planning Using the GE/McKinsey Approach at Addison Wesley Longman Case
216(1)
Background
216(4)
The new marketing texts
217(1)
The new marketing book promotional challenge
217(1)
Applying the GE approach
217(3)
Appendix: Details of the Three Books from AWL Promotional Material
220(3)
Portfolio Analysis Exercise
223(3)
Jenny's Gelato Case
226(5)
ACME Liquid Cleanser Exercise
231(1)
Background
231(1)
The Compete Model
231(2)
PART III Developing Marketing Programs 233(229)
New Product Decisions
233(69)
Introduction
233(3)
New Product Decision Models
236(3)
Models for identifying opportunities
236(2)
Models for product design
238(1)
Models for new product forecasting and testing
239(1)
Conjoint Analysis for Product Design
239(14)
Introduction
239(3)
Conjoint analysis procedure
242(8)
Other enhancements to the basic conjoint model
250(1)
Contexts best suited for conjoint analysis
251(2)
Forecasting the Sales of New Products
253(10)
Overview of the Bass model
253(2)
Technical description of the Bass model
255(6)
Extensions of the basic Bass model
261(2)
Pretest Market Forecasting
263(8)
Overview of the ASSESSOR model
264(2)
The preference model
266(2)
Trial-repeat model
268(3)
The validity and value of the ASSESSOR model
271(1)
Summary
271(1)
Forte Hotel Design Exercise
272(1)
Forte Executive Innes
272(1)
Company Background
272(1)
Preliminary Evaluation
272(5)
Conjoint Analysis (Matching hotel attributes to customer preferences)
274(3)
Zenith High Definition Television (HDTV) Case
277(1)
HDTV Background
277(2)
Zenith HDTV Efforts to Date
279(1)
The TV Market
279(2)
Forecasts of HDTV Sales
281(2)
Johnson Wax: Enhance Case (A)
283(1)
Instant Hair Conditioner
283(1)
S.C. Johnson & Company
283(1)
New-Product Development at Johnson Wax
284(1)
The Hair Conditioning Market
284(1)
Agree
285(1)
Enhance Product Development
286(1)
The ASSESSOR Pretest Market
286(2)
ASSESSOR Results
288(4)
Trial and repeat model
290(1)
Preference model estimates of share
291(1)
Recommendations
292(10)
Advertising and Communications Decisions
302(52)
The Bewildering Nature of Advertising
303(1)
Advertising Effects: Response, Media, and Copy
304(6)
Advertising response phenomena
304(4)
Frequency phenomena
308(1)
Copy effects
309(1)
Advertising Budget Decisions
310(9)
Media Decisions
319(5)
Advertising Copy Development and Decisions
324(11)
Copy effectiveness
324(3)
Estimating the creative quality of ads
327(1)
Advertising design
328(7)
Summary
335(1)
Blue Mountain Coffee Company Case
336(1)
Blue Mountain's Market Position
336(1)
Operation Breakout
337(3)
Planning for Fiscal Year 1995
340(3)
The market planning model
340(1)
Recent developments: The U.S. coffee market in transition
341(2)
Convection Corporation Case
343(1)
Using a Communication Planning Model to Aid Industrial Marketing Budget Decisions
343(1)
Background
343(4)
Heatcrete 4000
344(1)
Ceratam
344(1)
Flowclean Sootblowers
345(1)
Corlin Valve
346(1)
ADVISOR: An Approach to Marketing Budget Planning
347(6)
Budget task force meeting
348(5)
Johnson Wax Ad Copy Design Exercise
353(1)
Salesforce and Channel Decisions
354(60)
Introduction to Salesforce Models
354(3)
Sales-response models for representing the effects of sales activities
354(2)
Salesforce management decisions
356(1)
Salesforce Sizing and Allocation
357(8)
Intuitive methods
357(2)
Market-response methods (the Syntex model)
359(6)
Extending the Syntex Model: Reallocator
365(1)
Sales Territory Design
366(3)
The GEOLINE model for territory design
367(2)
Salesforce Compensation
369(4)
Using conjoint analysis to design a bonus plan (the MSZ model)
370(3)
Improving the Efficiency and Effectiveness of Sales Calls
373(6)
The CALLPLAN model
373(6)
Marketing Channel Decisions
379(5)
The gravity model
379(5)
Summary
384(2)
Syntex Laboratories (A) Case
386(1)
Company Background
386(1)
Syntex Laboratories
386(1)
Syntex Labs' Product Line
387(1)
Naprosyn
387(1)
Anaprox
387(1)
Topical Steriods
387(1)
Norinyl
388(1)
Nasalide
388(1)
The Sales Representative
388(1)
Sales Management at Syntex Labs
389(2)
Sales Force Size
389(1)
Call Frequency
390(1)
Allocation of Sales Efforts Across Products and Physician Specialties
390(1)
Geographic Allocation of Sales Force
390(1)
Sales Force Strategy Model
391(18)
Model Development Process
392(1)
Defining the model inputs
392(1)
Model Structure
393(2)
Results of the SSM Analysis
395(1)
Management implications
395(14)
The John French Exercise: Sales Call Planning for UBC (CALLPLAN)
409(2)
J&J Family Video Case
411(3)
Price and Sales Promotion Decisions
414(48)
Pricing Decisions: The Classical Economics Approach
414(4)
Pricing in Practice: Orientation to Cost, Demand, or Competition
418(6)
Cost-oriented pricing
418(1)
Demand-oriented pricing
419(3)
Competition-oriented pricing
422(2)
Interactive Pricing: Reference Prices and Price Negotiations
424(2)
Price Discrimination
426(8)
Understanding price discrimination
426(2)
Geographic price discrimination
428(1)
Temporal price discrimination
429(4)
Nonlinear pricing or quantity discounts
433(1)
Other forms of price discrimination
434(1)
Pricing Product Lines
434(1)
Sales Promotions: Types and Effects
435(5)
Objectives of Promotions
436(1)
Characteristics of promotions
436(4)
Aggregate Models to Analyze Promotional Effects
440(4)
Analyzing Individuals' Responses to Promotions
444(4)
Summary
448(1)
Account Pricing for the ABCOR2000 Exercise
449(1)
Background
449(2)
The value spreadsheet
450(1)
Price Planning for the ABCOR2000 Exercise
451(1)
The Problem
452(1)
Paving I-99 Exercise
453(2)
Part 1: Training Exercise
453(1)
Part 2: The bid-competition simulation
454(1)
Forte Hotel Revenue Management Exercise
455(1)
How the Generalized Revenue Model Works
456(2)
Massmart Inc. Case
458(1)
Background
458(1)
Scanner-Panel Data
459(1)
The Promotion Model
460(2)
PART IV Conclusions 462(19)
Marketing Engineering: A Look Back and a Look Ahead
462(19)
Marketing Engineering: A Look Back
462(3)
Using Marketing Engineering Within Firms
465(2)
Marketing Engineering: A Look Ahead
467(13)
Postscript
480(1)
References 481(18)
Subject Index 499(12)
Company Index 511(4)
Name Index 515

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