New way to measure consumers’ judgment

1. New way to measure consumers’ judgment Jack Antes Geoffrey Rabinovich Milia Shang

2. Authors Paul E. Green Yoram Wind (1927-2012) A marketing professor at the Wharton School of the University of Pennsylvania and a prolific writer. He wrote more than 160 books and 1,400 articles on the marketing field. Academic Director, The Wharton Fellows Program. Author of 22 books and more than 250 research papers, articles and monographs on marketing

3. Considerations for new or existing product • Know the market: Consumer preferences, choices, alternatives, needs, wants, etc. • Understand nature of product: Qualities, attributes, etc.

4. Problem What consumer really wants? • Product has various attributes. • Consumer overall judgment about the value of characteristics. Researches developed a new measurement technique called:

5. Conjoint Analysis • Consumer over judgment about set of alternatives. • Decompose evaluations into separate, compatible scales. Help managers evaluate the relative importance of various attributes of the product.

6. Product. • Product most important attributes that influence consumer preference. • Find the number of alternatives (all possible combinations). • Experiment design Orthogonal array. • Computing the utilities. • Importance of attributes. • Managerial Implications.

7. Orthogonal Array Considered system with: 3 parameters and each with 3 possible combinations 3x3x3= 27 test cases. Use orthogonal array to test only 9 combinations Combinations are selected and the in depended contribution of all factors are balanced. Each factor weight is separated from, and not confuse with other factors.

8. Orthogonal array: 3x3x3x2x2= 108 alternatives after orthogonal array 18 combinations were tested.

9. Computing the utilities • Computing scales of each attribute. • How important each attribute is to the consumer. • All ranked data enter to the program. • Computer search from scale of value for each factor.

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

11. Managerial implications • How these results cam be used in the design of product/marketing strategy. • Design and price of spot remover. • Packed design with mid price and money back warranty.

12. Air Carrier Study • Small difference between B-707 & B-747 • Main factors: • Departure time • Punctuality of arrival • Number of stops • Attitudes of flight attendants

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

14. Potential Uses • Consumer evaluations can be obtained on: • New product formulations • Package design, brand & promotion • Pricing & brand alternatives • Verbalized descriptions of new products • Alternative service designs

15. Explicit Judgmental Criterion • Best value for the money • Convenience of use • Suitability for a specified type of consumer or for a specified end use • “Psychological images”: Ruggedness, distinctiveness, conservativeness

16. Designing Bar Soaps • Related psychological imagery of physical characteristics to end-use appropriateness • Type of fragrance was the most important physical variable • Illustrated the feasibility of translating physical variables to psychological variables

17. Verbalized Descriptions of New Concepts • Principal factors of interest: gas mileage, price, country of manufacture &etc. • Customers evaluated factor levels on a two-at-a-time basis

18. Organizations as Consumers • Evaluation of organizational buyer are the most important inputs to industrial marketing strategy. • Study conduct to assess how physicians value various characteristics of a clinical laboratory • Emphasize convenience factors in addition to its focus on test reliability

19. Marketing Simulators • 25 service factors • Utility functions varied as expected • Discovered perceptions of consumers • Utility functions and perceptions used in simulator • Simulator results

20. Prospect and Limitations • Limited experimentation • Limited success • Effectiveness of model • Essence of product and service may not be captured • Flexibility

21. Factor Analysis • Attributes provided by researcher • Objective is to find commonalities in factors

22. Perceptual Mapping • Use consumer judgments • Find objects that are similar • Results

23. Cluster Analysis • Used to find homogeneous groups • Must analyze segment and determine variables to be measured

24. Cluster Example • Over 50 consumer in UK • 200 Statements • 1700 samples • Narrowed to 7 for analysis

25. Multiple Regression • Compile explanatory variables to identify a response variable • Example: Sales forecasting for cable subscribers • Y=number of subscribers • X=Advertising rate for one minute of prime time • X=Kilowatt power • X=# of families in living area of coverage • X=Number of competing stations

26. Discriminant Analysis Example Identify lung cancer: Yes or no outcome Run tests (predictor variables) Based on predictor variables we get results to validate one option • Develop criterion variables which are categorical • Based on criterion develop predictor variables • Criterion variables must fall into two groups

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