Years of research experience came together in Ely Dahan’s (UCLA Medical School plus a tone of other academic qualifications) presentation, plus the synthesizer mind-set that fosters new ways of shaking up old methodologies to fit new contexts and creating a medley with crowd-sourced data. What we thought we knew about conjoint analysis Dahan has eclipsed with bolder, crisper adaptations of the choice-based approaches.
The most compelling application of Dahan’s approach was that of presenting treatment options to a patient with prostrate concerns. The power of this approach stems from its use of preferences that the patient has expressed through a choice survey. That is, the one-page treatment report that is provided to the patient has been shaped by the patient’s own values. Instead of the conventional considerations about remaining years of life trade-offs, the options report emphasizes those considerations that the patient has identified as having the most meaning and value to him personally.
Individual conjoint recommendations, according to Dahan, represent personal insights, they are engaging and graphic, and they are adaptive because they are individual. Instead of using the long lists of attributes or bundles of attributes that are characteristic of conjoint analysis, Dahan’s choice interface gives respondents the opportunity to choose product items as a whole. Real products in conjoint stimuli are more appealing and more representative of real life choice-making. The process is to populate the universe of stimuli attributes, and use a cluster analysis design to establish choices. Naturally, you know that this friendly interface is cover for very sophisticated orthogonal algorithms.
Dahan provided accessible and compelling examples of mapping of people, products, and preferences by combining different methodologies. His recommender roadmap looks like this:
· Choice-conjoint Interface – more natural, more real life
· Accounting for Taste – use crowd sourcing
· Real Product Stimuli (real world is not bundles of attributes)
· New Adaptive Methods – speed up process & reduce size of survey
· Data: People & Products – harness big data choices
Want to know more about how to refine your choice and conjoint processes? Check out this article: https://faculty.fuqua.duke.edu/~mela/BA561/Bodapati,%20Anand%20and%20Sachin%20Gupta%20%282004%29.pdf
Gigi DeVault writes a market research column for About. com.
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