Conjoint Conjoint Adaptive Ranking Database System Adaptive Ranking Database System ( ( CARDS CARDS ) ) Ely Dahan Ely Dahan Michael Yee, John Hauser & Jim Michael Yee, John Hauser & Jim Orlin Orlin EXPLOR Award Winning Presentation – September 22, 2004 EXPLOR Award Winning Presentation – September 22, 2004 Good, Fast, Cheap Good, Fast, Cheap and and Easy? Easy?
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Conjoint Adaptive Ranking Database System ( CARDS )
Good, Fast, Cheap and Easy?. Conjoint Adaptive Ranking Database System ( CARDS ). Ely Dahan. Michael Yee, John Hauser & Jim Orlin. EXPLOR Award Winning Presentation – September 22, 2004. The Problem. Current methods require many questions for few answers - PowerPoint PPT Presentation
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ConjointConjoint Adaptive Ranking Database SystemAdaptive Ranking Database System ( (CARDSCARDS))
Ely DahanEly Dahan
Michael Yee, John Hauser & Jim OrlinMichael Yee, John Hauser & Jim Orlin
EXPLOR Award Winning Presentation – September 22, 2004EXPLOR Award Winning Presentation – September 22, 2004
• Simplifying rules to narrowchoices not typically captured
• Respondents make mistakesdue to fatigue, causing inconsistency
• Is there a better way?
Smart Phone ExampleSmart Phone Example
SmallSmallServiceService
Phone BrandPhone Brand
Example: Smart Phone• Respondent: Alex Bell• How does Alex choose
a smart phone?
Mini KeyboardMini Keyboard
FlipFlip 1010
55
7766
99 Utility Scores:Utility Scores:Alex makes tradeoffsAlex makes tradeoffs
SmallSmallServiceService
Phone BrandPhone Brand
• Respondent: Alex Bell• How does Alex choose
a smart phone?
Mini KeyboardMini Keyboard
FlipFlip 1616
11
4422
88 Process of Elimination:Process of Elimination:Focus on key featuresFocus on key features
Example: Smart Phone
Consider this tough task:Rank 32 Smart Phones based on your preferences
There are a billion, billion, billion, billionbillion, ways for a respondent to rank 32 smartphones!
Are weAre wesurprised thatsurprised that
respondents becomerespondents becomefatigued and makefatigued and make
mistakes!?mistakes!?
Prior Research on Adaptive Questioning• Johnson (1987, 1991) & Orme and King (‘02) Sawtooth ACA• Huber and Zwerina (1996), Aggregate utility balance• Arora and Huber (2001), Aggregate customization• Sandor and Wedel (2001), Aggregate + prior beliefs• Louviere, Hensher, and Swait (2000), Aggregate CBC
Prior Research on Fast & Frugal Rules• Tversky (1969, 1972), lexicographic semi-order, elimination by aspects• Dawes and Corrigan (1974), unit weights, linear models• Montgomery and Svenson (1976), 2-stage processing• Thorngate (1980), efficient decision heuristics• Shugan (1980), cost of thinking (pair wise comparisons)• Johnson, Meyer, et. al. (1984, 1989), protocol anal., choice models can fail• Roberts and Lattin (1991, 1997), two-stage w/greedy• Gigerenzer and Goldstein (1996), Take the Best & others• Bettman, Luce, Payne (1996, 1998), Accuracy vs. effort, lexicography• Martignon and Hoffrage (2002), fast and frugal is robust
Two new ideas:
• IDEA 1: We can now measure Alex’s process of elimination
• IDEA 2: We can help Alex avoid inconsistent answers
Customer Insight:Respondents may be using a simple
process of eliminationprocess of eliminationto narrow choices for consideration
IDEA 1:
Phone BrandPhone BrandMini KeyboardMini Keyboard
FlipFlip
“I will only considerflip phones, with mini-keyboards, from Blackberry”
Customer Insight:Respondents may be using a simple
process of eliminationprocess of elimination
IDEA 1:
How hard is it to identify each respondent’s simplifying rule?
AGB
How can we identify each respondent’s
process of eliminationprocess of elimination
IDEA 1:
?
•Tougher than it seems, because they may be using one of a huge number of possible rules
•We solved this problem with a new computer technique (speedy)
•We tested our theory and it works!
The big benefit of identifying respondents’
process of eliminationprocess of elimination?
•GoodGood Accuracy, customer insight
•FastFast 1 minute for them, quick for us
•CheapCheap Pack more into the same study
•EasyEasy Reduce drudgery
RankSome
RankAll
2 minutes 7 minutes
2 7
Process of elimination Benefit: CheapCheap
Could you use 5 extra minutes of survey time?Could you use 5 extra minutes of survey time?
FastFast
Ranksome
Rankall
kind of funokay
Somewhatinteresting
about rightlong
Benefit: EasyEasy
How do we know if theprocess of elimination
idea is
GoodGood?
Holdout sample for rankings
Pretty GOODGOOD
Holdout sample for first choice
Pretty GOODGOOD
The consistency criterion,a new approach
Reduce response error by “guiding” respondents towards consistent answers
Each choice must be 100% consistent with at least one set of utility scores
IDEA 2: Avoiding inconsistent answers
• Show product features
• Click on favorite cards
• Inconsistentcards just“disappear”
• GetUtilityscores
• Save lotsof clicks
Keeping people consistent:Conjoint Adaptive Ranking Database System (CARDSCARDS)