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.