1. New Ways to Measure Consumers’ Judgments
Green, Paul E. and Yoram Wind (1975), “New Ways to Measure Consumers’ Judgments, “Harvard Business Review, July-August,
Please consider reading my handout “advance research methods” while studying this article. Power points for the handout are in blackboard and on the web

2. Authors Wharton School Professor of Marketing
Expert in mathematics and statistics
12 years of Industry experience
Author of 160 books and 1400 articles
Paul Green
Wharton School Professor of Marketing
Expert in buyer behavior and market research
Editorial Board Member: Journal of Marketing, Journal of Business Research
Author of 22 books and 250 research papers
Yorum Wind

3. Outline of the Article
The article discusses conjoint analysis and other multivariate techniques used in business/marketing.
Conjoint analysis
Multiple regression
Factor analysis
Perceptual mapping
Cluster analysis
Discriminant analysis
This power point presentation also includes materials from my handout “Advance Research Methods.”

4. Conjoint Analysis
Conjoint analysis is “a new measurement technique from the fields of mathematical psychology and psychometrics that can aid the marketing manager in sorting out the relative importance of a product’s multidimensional attributes.”
It starts with the consumers’ overall judgments about a set of complex alternatives, and, then decomposes consumers’ original evaluations into separate and compatible utility scales from which the original global judgments can be reconstituted.

5. How Consumer Measurement Works
Consumers rate three designs on the basis of 5 factors. Package design, brand name, and price have 3 levels. Good housekeeping seal and money back guarantee has 2 levels. A total of 18 consumer cards are used giving a combination of 108 (3x3x3x2x2) alternatives. Consumers are asked to rank the cards. Each card is a combination, an orthogonal array, a point in a multidimensional space; it is a choice based on utilities.

6. Importance of attributes
Utility combination 18 is 3.6
Package: C (0.6)
Brand: Bissell (0.5)
Piece: $ 1.19 (1.0)
Good Housekeeping: Yes (0.3)
Money-back: yes (0.7)
All utility scale have same unit
Relative importance of one factor depends on the levels included in the design
Packed design B highest utility

7. Air Carrier Study Example
Factors to evaluate
Aircraft/Carrier
Departure time relative to ideal
Punctuality of arrival
Passenger load
Number of stops en route
Attitudes of flight attendants
Entertainment
Findings of the study
Two factors comprised the biggest utility differences: punctuality of arrival and attitudes of flight attendants
Utility difference between the two jet planes is very small
Other factors to consider: departure time and number of stops

8. Replacement Tire Study Example
Design to protest TV commercials for sponsor’s brand tires
Brand name did not play important role
Tread mileage & price are important

9. Potential Use and Limitations
Can be useful in evaluating consumer judgments for….
New product formulations
Package design, brand and promotion
Pricing and brand alternatives
Verbalized descriptions of new products
Alternative service designs
Limitations include…
Number of attributes is too large
Too new method
Not fit all products and services
Not all product can be decomposed

10. Multiple Regression
Compile explanatory variables to identify a response variable.
Sales forecasting for cable subscribers (Y).
Y=number of subscribers
X1=Advertising rate for one minute of prime time
X2=Kilowatt power
X3=Number of families in living area of coverage
X4=Number of competing stations

11. Factor Analysis Data reduction technique
Used to determine the underlying dimensions/factors defining the attributes/variables
Attributes provided by researcher
Objective is to find commonalities in factors

12. Perceptual Mapping Use consumer judgments
Find objects that are similar
Very helpful in brand positioning

13. Cluster Analysis Used to determine homogeneous groups
Used in segmentation and profiling
Clusters are based on similarity

14. Discriminant Analysis
Develop criterion variables which are categorical
Based on criterion develop predictor variables
Criterion variables must fall into two groups
Identify lung cancer: Yes or no outcome
Run tests (predictor variables)
Based on predictor variables we get results to validate one option
Can we predict how many people will go bankrupt in Texas next year?

15. Discussion Questions
What is conjoint analysis? What are the common applications and limitations of conjoint analysis? How can we overcome its limitations?
Why should marketers study multivariate analysis techniques? Define/elaborate various techniques we discussed in the class and explain how they help marketers make “informed decisions.”