About Surveys

Max-Diff is a method of scaling in which respondents are asked to identify the most important attribute and least important attribute for a set of attributes.  It counts down significantly on the amount number of questions that need are asked in comparison to the Paired Comparisons technique.  It is based on a measure of customer choice and trade-off, instead of typical rating scale responses.  It can be used to generate importance or preference scores for multiple items such as brands, concepts, or attributes.

Basically, it works like this:

A respondent is shown a set of attributes;

      A  B  C  D

And are asked to identify the most important attribute and the least important attribute (They say A is most importand and D is least important).  From this one question we know five of the six paired comparisons:

         A>B, A>C, A>D, B>D, C>D.

The analysis of Max-Diff can be done using a number of different algorithms and from these we can estimate utility functions.  Probably the most commonly used algorithm to analyze Max-Diff is using a Hierarchal Bayesian procdure.  Hierarchal Bayes is beneficial because it allows for borrowing across the data.

 Qualtrics surveys is developing this functionality.

This entry was posted by craigl on Tuesday, May 6th, 2008 at 3:25 pm and is filed under Statistical Methods, Market Research, Qualtrics.