Conjoint Online

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Matching Candidates with Job Openings

Online feedback from conjoint interviews satisifies respondents' intrinsic motivation

Which conjoint method should I use?

Learn more about Adaptive Conjoint Analysis

What is Conjoint?
Conjoint data collection and analysis was introduced to the market research community in the mid-1960s. It was based on academic work in psychometrics conducted at Bell Labs, Princeton, Univ. of North Carolina and other institutions.

The premise of conjoint data collection is that by asking respondents to state their preferences among alternative products that systematically vary in their features, researchers can "discover" each respondent's underlying "utilities" for product features. A typical conjoint data collection procedure in the '70s and '80s would be to design 30 or more cards, each representing various collections of product features. Respondents would sort the cards from most to least desirable. From the rankings, each respondent's utilities can be calculated.

By forcing respondents to "trade off" product features for each other, conjoint data collection provides more realistic guidance for product development than simply asking for importance ratings.

What is Adaptive Conjoint?
Adaptive Conjoint Analysis (ACA) is a "hybrid" data collection technique that combines self-explicated importance ratings with pair-wise trade-off tasks. The ACA algorithm was programmed by Rich Johnson of Sawtooth Software, Inc. (SSI) in 1985. It has worked quite satisfactorily on DOS computers ever since.

ACA has the virtue of allowing for relatively larger conjoint designs than could be handled by other conjoint methods. It does this by first asking respondents for explicit importance ratings (the "priors" section), followed by trade-off tasks that only include those attributes and levels each respondent rates as most important. Thus, the interview is tailored to each respondent.

What's the relationship between Conjoint Online and Sawtooth Software, Inc.?
In 1998, Conjoint Online re-programmed the interviewing module of ACA so that it would work in an Internet environment. The conversion was based on the C source code for ACA's interviewing module.

Conjoint Online doesn't sell software, but provides the conjoint application to users who don't want to purchase the ACA software or who don't want to install and maintain it on their web site. Conjoint Online also provides support services, including free pretesting, so that users can enjoy the benefits of conjoint quickly and at low cost.

Is the Conjoint Online implementation of ACA the same as SSI's?
Conjoint Online produces identical results -- because it uses the SSI algorithm. However, SSI's ACA has many features that are infrequently used. As users need some of the esoteric features, Conjoint Online has added them.

Also, Conjoint Online has introduced an option to the ACA algorithm that makes it more suitable for situations where individual feedback is important. In the original ACA algorithm, reversals could occur in unimportant attributes. For example, if you had a slight preference for a blue over a black car, during the pairs section, ACA can sometimes become confused and think you prefer a black car. ACA might then ask you whether you'd prefer a blue car at a lower price to a black car at a higher price. Since you prefer blue to black anyway, you might think the computer slipped a cog. As this can be confusing to respondents, Conjoint Online has an option to prevent reversals from occuring.

In practice, reversals don't matter much if you are doing aggregate analysis (grouping respondents). However, if you want to present a respondent's results back to him/her, prohibiting reversals can be useful.

Example of Individual Level Analysis
Matching Candidates with Job Openings
(Man Jit Singh and Sam Kingsley, Sawtooth Software Conference, February 1999)

The authors demonstrated how ACA is being used on the Web in matching potential job candidates with job openings. Sing and Kingsley are the first to develop a Web-enabled version of ACA based on Sawtooth Software's underlying code. To date, hundreds of thousands of applicants have completed their ACA survey on job preferences on the Web.

According to the authors, "the job search and recruiting business has traditionally relied on the 'telephone tree'", followed by a detailed review by senior associates, follow-up interviews, offers and counter-offers. By collecting much information up-front in a standard survey, followed by a more detailed assessment of the tradeoffs (ACA) each applicant makes regarding compensation and other job-related elements, a large number of applicants can be sorted through efficiently.

Because the level of analysis is at the individual, part worth reversals can be problematic. While ACA generally results in fewer reversals than other conjoint methods, they still can occur. Simply averaging and "tieing" procedures are one suggested remedy. [Read more >>]


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