1 / 15

Preference Elicitation [Conjoint Analysis]

Preference Elicitation [Conjoint Analysis]. Conjoint Analysis. Market research: assess consumer’s preferences on homogenous class of products . Approach: describe products in terms of attributes and levels [conjoint structure]. . Example: Cars = (Max.Speed) x (Gas Mileage)

baird
Télécharger la présentation

Preference Elicitation [Conjoint Analysis]

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Preference Elicitation [Conjoint Analysis]

  2. Conjoint Analysis Market research: assess consumer’s preferences on homogenous class of products Approach: describe products in terms of attributes and levels [conjoint structure]. Example: Cars = (Max.Speed) x(Gas Mileage) Max. Speed = { 100 mph, 120 mph, 150 mph} Gas Mileage = { 20 mpg, 17 mpg, 13 mpg, 10 mpg}

  3. 150 mph 10 mpg 100 mph 20 mpg Pairwise Comparsions Which car are you more likely to buy? • 100 mph • 13 mpg • 120 mph • 17 mpg Tradeoff!

  4. Marketing Approach • Given a set of products X • Elicit consumer’s preferences from pairwise comparisons [simulates real choice tasks] • Only small [constant] number of questions per respondent • For each respondent value function v: X →[0,1]

  5. Optimizing Visualization Systems Which (volume) rendering shows more detail?

  6. Optimizing Visualization Systems Which (volume) rendering do you like better?

  7. Optimizing Visualization Systems Which (volume) rendering shows more detail?

  8. Optimizing Visualization Systems Which (volume) rendering shows more detail?

  9. Netflix Challenge

  10. Netflix Challenge http://www.netflixprize.com/index

  11. Netflix Challenge

  12. Netflix Challenge • Challenge: From given ratings predict rating of unrated movies. • Training data set: >100 million ratings from >480 thousand customers on ~18 thousand movies. • Test data: 2.8 million customer/movie pairs with the ratings withheld. • Compare to Netflix’ predictor ‘Cinematch’ • Quality measure: root mean square error

  13. Surface Reconstruction

  14. Surface reconstruction

  15. Surface Reconstruction

More Related