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McGraw-Hill/Irwin

McGraw-Hill/Irwin. © 2003 The McGraw-Hill Companies, Inc., All Rights Reserved. CHAPTER SIX. ANALYTICAL ATTRIBUTE APPROACHES: INTRODUCTION AND PERCEPTUAL MAPPING. What are Analytical Attribute Techniques?.

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McGraw-Hill/Irwin

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  1. McGraw-Hill/Irwin © 2003 The McGraw-Hill Companies, Inc., All Rights Reserved.

  2. CHAPTER SIX ANALYTICAL ATTRIBUTE APPROACHES: INTRODUCTION AND PERCEPTUAL MAPPING

  3. What are Analytical Attribute Techniques? • Basic idea: products are made up of attributes -- a future product change must involve one or more of these attributes. • Three types of attributes: features, functions, benefits. • Theoretical sequence: feature permits a function which provides a benefit.

  4. Gap Analysis • Determinant gap map (produced from managerial input/judgment on products) • AR perceptual gap map (based on attribute ratings by customers) • OS perceptual map (based on overall similarities ratings by customers)

  5. A Determinant Gap Map Figure 6.2

  6. A DataCube Figure 6.3 700 . . . Respondents 2 1 1 2 3 .... Options .... X Ideal 1 2 . . . . . . . 15 Attributes

  7. Obtaining Customer Perceptions Figure 6.4 Rate each brand you are familiar with on each of the following: Disagree Agree 1. Attractive design 1..2..3..4..5 2. Stylish 1..2..3..4..5 3. Comfortable to wear 1..2..3..4..5 4. Fashionable 1..2..3..4..5 5. I feel good when I wear it 1..2..3..4..5 6. Is ideal for swimming 1..2..3..4..5 7. Looks like a designer label 1..2..3..4..5 8. Easy to swim in 1..2..3..4..5 9. In style 1..2..3..4..5 10. Great appearance 1..2..3..4..5 11. Comfortable to swim in 1..2..3..4..5 12. This is a desirable label 1..2..3..4..5 13. Gives me the look I like 1..2..3..4..5 14. I like the colors it comes in 1..2..3..4..5 15. Is functional for swimming 1..2..3..4..5

  8. Snake Plot of Perceptions (Three Brands) Figure 6.5 Ratings Aqualine Islands Sunflare Attributes

  9. Data Reduction Using Multivariate Analysis • Factor Analysis • Reduces the original number of attributes to a smaller number of factors, each containing a set of attributes that “hang together” • Cluster Analysis • Reduces the original number of respondents to a smaller number of clusters based on their benefits sought, as revealed by their “ideal brand”

  10. Selecting the Appropriate Number of Factors Figure 6.6 The Scree Percent Variance Explained No. of Factors

  11. Factor Loading Matrix Figure 6.7

  12. Factor Scores Matrix Figure 6.8 Sample calculation of factor scores: From the snake plot, the mean ratings of Aqualine on Attributes 1 through 15 are 2.15, 2.40, 3.48, …, 3.77. Multiply each of these mean ratings by the corresponding coefficient in the factor score coefficient matrix to get Aqualine’s factor scores. For example, on Factor 1, Aqualine’s score is (2.15 x 0.145) + (2.40 x 0.146) + (3.48 x -0.018) + … + (3.77 x -0.019) = 2.48. Similarly, its score on Factor 2 can be calculated as 4.36. All other brands’ factor scores are calculated the same way.

  13. Comfort Aqualine Gap 1 Islands Molokai Fashion Splash Sunflare Gap 2 The AR Perceptual Map Figure 6.9 2 -2 2 -2

  14. Dissimilarity Matrix Figure 6.10

  15. Aqualine Comfort Molokai Islands Fashion Sunflare Splash The OS Perceptual Map Figure 6.11

  16. Comparing AR and OS Methods Figure 6.12 Source: Adapted from Robert J. Dolan, Managing the New Product Development Process: Cases and Notes (Reading, MA: Addison-Wesley, 1993), p. 102.

  17. Failures of Gap Analysis • Input comes from questions on how brands differ (nuances ignored) • Brands considered as sets of attributes; totalities, interrelationships overlooked; also creations requiring a conceptual leap • Analysis and mapping may be history by the time data are gathered and analyzed • Acceptance of findings by persons turned off by mathematical calculations?

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