Sawtooth Solutions #10: 1999 Summer

Eighth Conference Planned for East Coast

The eighth Sawtooth Software Conference will be held on March 21-24, 2000 on Hilton Head Island, South Carolina. Hilton Head is an upscale island resort community off the southern coast of South Carolina. This is the first time we have held our conference on the East Coast. We hope that those of you who have been waiting for us to meet on the East Coast will take advantage and attend.

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Scaling Conjoint Part Worths: Points vs. Zero-Centered Diffs

For over a decade, a re-scaling method called "Points" has been the default for reporting conjoint part worths (utilities) in Sawtooth Software's conjoint simulators. This approach gives equal weight to each respondent by making the total sum of part worths equal to the number of attributes times 100. Since conjoint part worths are scaled to an arbitrary constant within each attribute, it seemed to us early on that setting the worst level of each attribute for each respondent to zero was as reasonable a decision as any. This held promise of making it easier to present part worths to clients, since the values would generally fall in a comfortable range of about 0 to 100 (the values can actually exceed 100). However, we now suspect that fostering familiarity has sometimes led to misinterpretation. With the benefit of years of hindsight, we think that Points was a mistake.

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Hierarchical Bayes Estimation and ICE Revisited

As you have probably noticed, hierarchical Bayes (HB) has been the subject of several favorable journal articles and many presentations at the more technical market research conferences. We expect that the amazing advances in the speed of computers will hasten the adoption of hierarchical Bayes algorithms not only for conjoint problems, but for other market research applications as well.

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Announcing Composite Product Mapping (CPM)

Perceptual Mapping has been a useful method for condensing what can often become a very large amount of ratings information (such as a matrix of brand ratings on different attributes) into a visual picture:

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CBC Version 2 Now Available

After more than two years of development, we are pleased to announce the release of Choice-Based Conjoint (CBC) v2 for Windows. Choice-Based Conjoint (sometimes called Discrete Choice) has gained significantly in popularity over the years. Rather than having respondents rank-order or rate product concepts (defined on multiple attributes) as with traditional conjoint analysis or ACA, respondents perform a task that better mimics what they do in the real world: they make choices within sets of available products. CBC has proven very useful for problems that involve about six or fewer attributes. CBC has particularly found use in pricing research studies, where it can estimate unique price sensitivities for distinct brands.

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