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New Way to Measure Consumers’ Judgments By Paul E. Green and Yoram Wind

New Way to Measure Consumers’ Judgments By Paul E. Green and Yoram Wind. Fall 2009 MKTG 5320 Group 6: Carla Pereira Juan Carlos Gomez Ryan Atwood Alex Ramirez Bill Wilson. Tonight We Will Cover…. Overview and “The Problem” Mechanics of Conjoint Analysis Example of Conjoint Analysis

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New Way to Measure Consumers’ Judgments By Paul E. Green and Yoram Wind

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  1. New Way to Measure Consumers’ Judgments By Paul E. Green and Yoram Wind Fall 2009 MKTG 5320 Group 6: Carla Pereira Juan Carlos Gomez Ryan Atwood Alex Ramirez Bill Wilson

  2. Tonight We Will Cover… Overview and “The Problem” Mechanics of Conjoint Analysis Example of Conjoint Analysis Managerial implications and extended examples Marketing strategy simulations and limitations Other consumer preference techniques

  3. Overview A marketing manager must consider two basic problems: What is the market? What is the nature of the product? Conjoint Measurement assists in understanding the nature of the product in the eyes of the customer

  4. Defining the Problem - A Product is a collection of attributes - A Customer selects a product based on the combination of attributes which most appeal to him/her HOW DOES THE MANAGER DECIDE WHICH ATTRIBUTES OF A PRODUCT ARE MOST IMPORTANT TO A CUSTOMER?

  5. Problem Examples Which flight would you rather take? B-737 flown by Southwest ($240) leaving Corpus Christi at 6:45am with 3 stops en-route to NYC and only a drink & peanuts served, only magazines provided. B-767 flown by Continental ($350) leaving San Antonio at 9:45am direct to NYC with a lunch served and two in-flight movies. Vs.

  6. Which tire would you rather buy? • Goodyear’s with a tread life of 30,000 miles at $40 and a 10 minute drive from your house • Firestone’s with a tread life of 50,000 miles at $85 and a 20 minute drive from your house

  7. Mechanics of Conjoint Measurement

  8. Attributes Attributes are the variable factors that will influence consumer preferences Attributes can have multiple levels For example 2 level factors vs. 3 level factors Total Alternatives To find the total number of alternatives by the number of different factors

  9. Orthogonal Array The Orthogonal Array is arrangement of selected alternatives The alternatives are selected in such a way that independent contributions of each factor is balanced so that its weight is kept separate from the others C A B

  10. Orthogonal Array

  11. Ranking of Alternatives Within the orthogonal array each possible alternative is ranked by consumers according to their likelihood of purchasing

  12. Computing Utilities Utility is a measure of satisfaction or desirability of various attributes A utility scale is computed to determine how influential each factor is in the consumer’s decision using only the ranked data. Utility is computed using a computer program so that a total utility is computed for each combination

  13. Total Utility Total utility is the sum of utilities for each factor level in a combination. Utilities can bee graphically displayed.

  14. UtilityGraph Retail Price Good Housekeeping Seal?

  15. Importance of Attributes Utility scores aid in product design and marketing by allowing managers to select the factor with the highest utility to influence consumers’ preferences Product designers will select attributes with the highest utility and eliminate others

  16. Package Design Brand Name Retail Price Good Housekeeping Seal? Money- Back Guarantee? Results of Comp. Analysis of Experimental Data of Exhibit I

  17. The Utility Ranges are: Package Design (1.0 – 0.1 = 0.9) Brand Name (0.5- 0.2 = 0.3) Price (1.0 - 0.1 = 0.9) Good Housekeeping seal (0.3 - 0.2 = 0.1) Money-Back Guarantee (0.7 - 0.2 = 0.5)

  18. Percent Relative Importance of Factors

  19. Managerial Implications

  20. Analysis Results: Influencing Design Desirable offering would be the one based on package Design B with money-back guarantee, a Good Housekeeping seal, and a price of $1.19 Retail Price Package Design Good Housekeeping Seal? Money- Back Guarantee?

  21. Analysis Results: Influencing Design Utility of a product at $1.39 is 0.3 less than one at $1.19. A money-back guarantee increases utility 0.5 Money- Back Guarantee? Retail Price

  22. Analysis Results: Influencing Design The use of a Good Housekeeping seal of approval adds a small amount of utility. Is not a significant contributor to the overall product attractiveness. Good Housekeeping Seal?

  23. Analysis Results: Influencing Design The utility of the three brand names serves as a quantitative benchmarking tool. Brand Name

  24. Air Carrier Study B-707 vs. B-747 *Value of flight length and service *Punctuality *Number of stops *Entertainment

  25. Punctuality of arrival Depart. time relative to ideal Air Carrier Study (Cont.) Utility difference between B-707 and B-747 is minimal Main factors = departure time, punctuality, stops, and attitudes of flight attendants.

  26. Number of stops in route Attitudes of flight attendants Air Carrier Study (Cont.)

  27. Replacement Tire Study Utility functions of respondents expressing interest in test commercials 5 brands with varying properties were exposed Tread mileage and price = important Brand name = not significant

  28. Marketing Strategy Simulations • One of the principal uses of Conjoint Measurement • Used to simulate: -consumer perceptions -evaluations in a period of time • Example: Consumer evaluations of Airline Services -25 different service factors: on-ground services, décor of cabins, seats, routing, price, etc. -Utility function: developed per route and purpose of flight

  29. Findings: • Estimated the market share effect for changes in service. • Examine effect of competitor’s actions. • Predicted changes in market share if due to changes in utility functions. • -Evaluations of consumer’s perceived service factors • -Overall perception of each airline • -Set the basis for building the model for the airline services simulation model

  30. Limitations: • Similar to other techniques • Minimal applications to emphasize capability of predicting sales and market share • Difficulty in representing certain products or services in utility functions and decision rules suitable for models • Unknowing assertiveness of approximation between simple vs. complex models • Limitations for representing alternatives of products/services through decomposition approach

  31. Generalized Benefits: • Allows to measure consumer trade-offs • Highly flexible dealing with the understanding of consumers’ challenges when deciding among for products or services

  32. Factor Analysis Around since 1940, Computers made it more practical due to the number of computations. To examine the commonality across various rating scales and find a geometric representation.

  33. Cluster Analysis Uses hierarchical tree. The sooner the objects group together to more closely related they are. Utilizes stimulus words to help the respondents get started thinking. Shampoo example.

  34. Multidimensional Scaling To detect meaningful underlying dimensions that help explain similarities or differences. MDS does not require linear relationships as does Factor Analysis. Uses: Ratings of similarity, percent agreement, and times a failure occurs.

  35. Multiple Regression To learn more about the relationship between independent and dependent variables. Utilizes a best fit line in a scatter plot to determine a linear regression to make predictions. Limitations in that it can only be used to find relationships.

  36. Discriminate Analysis Used to determine whether groups differ with regard to the average of a variable. Aids in prediction of outcome between subjects based on variable traits among the group. Analyzing multiple groups: Graduates that go to college vs. do not go. Do nots: Get a job vs trade school

  37. A product has multiple attributes and it is difficult to determine which attribute a customer perceives as most important Conjoint Measurement allows the marketing manager to determine which attributes a customer desires and the relative importance of one attribute over another. Conclusions Question #1

  38. Utility Function – provides a score relative to another item in the same attribute category Utility Range – provides a score of one attributes importance relative to different attributes. Conjoint Measurement has multiple uses to include: New product formulations Package design & Brand name selection Pricing decisions Verbalized descriptions Alternative service designs Conclusions (Cont.) Question #1 & 2

  39. Conclusions (Cont.) • Limitations • Some Products may involve utility functions and decision rules that may not be adequately captured. • Too many attributes to add together. • The essence of some products and services may not be well captured by a decomposition approach. • Artistic products where the whole exceeds the sum of its parts. Question #2 ? ? ? ? Vs. Vs. ? ?

  40. Conclusions (Cont.) Question #2 • Limitations • Limitation can be overcome through the use of other multivariate techniques. • *Factor Analysis *Multiple regression Analysis • *Cluster Analysis *Discriminate Analysis • *Multidimensional scaling

  41. “Informed Decisions” can be made because the marketer is able to understand how the customer perceives the product and make a decision based on the customers viewpoint Conclusions (Cont.) Question #3

  42. Any Questions ?

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