New Ways to Measure Consumer Preferences

1. New Ways to Measure Consumer Preferences Nicole Levy Etienne Couret Nguyen Le Xuan Phuong Kristen McCarty

2. Conjoint Measurement • Conjoint measurement is a technique which uses fields of mathematical psychology and psychometrics to • analyze consumer’s preferences • among multidimensional • attributes of a product or a • service

3. How the technique works • First, determine relevant attributes • Second, classify levels of • each attribute • Third, combine attribute • levels

4. How the technique works • Fourth, describe each combination and print on index card • Fifth, provide index cards to subjects; Subjects rank cards from most to least preferred

5. Identify Attributes • Combine alternatives to create possible product combinations Steps Illustrating Conjoint Measurement • List sample combinations on index cards • Respondents rank combinations in order of likelihood of purchase • Utility scales are computed • Use findings in product design and marketing strategies • Compare utility ranges to gauge relative importance of factors

6. Sample Combinations Ranked in Order of Likelihood of Purchase • 1 • 5 • 6 • 2 • 3 • 4

7. Sample Airline Utility Functions

8. Incorporate Findings into Market Strategy

9. Additional Uses of Conjoint Measurement Predicting sales and market share regarding the consumer’s evaluation of attributes Identifying market segmentation through consumer’s evaluation Expanding market share by discovering unfilled attribute combinations

10. Possible Uses of Conjoint Measurement • Determining combinations of possible attributes that could add more value; Based on specifying individual’s value system • Evaluating the importance of each attribute, for consumer preferences

11. Limitations to Conjoint Measurement No standard approach to determine attributes and their levels If amount of attributes/levels are large, the number of attribute-level combinations increases, and makes test more complex

12. Additional Limitations to Conjoint Measurement Conjoint measurement cannot be used with some products or services Verbal descriptions of each combination may not be clear; Can create confusion of subjects

13. Additional Techniques Factor Analysis Used since 1940’s Not sophisticated until arrival of computer Typical input Respondents’ subjective ratings of brands or services based on attributes Attributes provided by researcher

14. Other Techniques • Perceptual Mapping: • -More recent, developed with Computer appearance • - Take consumer judgment of overall similarity and preference • Find picture where objects judged similar are placed in a geometric space • - Here, consumers can choose their own frame of reference

15. Other Techniques Perceptual mapping: - Integrate ideal point of consumers - Can find point of preferences (ideal points close to products or identify sector preferred by consumers)

16. Additional Techniques to Measure Consumer Preferences • Cluster Analysis: • - Identify consumer judgment • - Hierarchical tree structure • - Similarity of attributes/ Come from left to right • - End at point where all attributes join together  Researchers assumed that the more a stimulus evoked another word, the more similar they were.

17. Benefits of Combining Techniques Factor Analysis &Perceptual Mapping - Perceptions Conjoint Measurement - Quantify trade off Cluster Analysis - Comparison techniques - Basis for grouping people

18. Combination of Techniques Techniques can be used in the same study Can detail different aspects of general types of input data

19. Questions?