Survey Analytics MaxDiff provides relative importance levels, not absolute ones. It is important, then, for the attributes to be chosen by those who have insight or prior knowledge about what the attributes of interest are likely to be. It is also important to ensure the complete set of options is included in the question set and that the respondent answers consistently. Unlike other conjoint or discrete choice methodologies, interaction terms are not modeled by MaxDiff. Max Diff output tends to be very strong on the most important variables, in addition you can get a enhanced analysis for the weaker variables paired with important variables.
Survey Analytics Max Diff AnalysisMaxDiff analysis can be used in new product features research or or even market segmentation research to get accurate orderings of the most important product features, Survey Analytics help's you discriminate among feature strengths better than derived importance methodologies. Like other trade-off analyses, the analysis derives utilities for each of the most important product features which can be used to derive optimal products, using market segmentation to put respondents into groups with similar preference structures, or to prioritize strategic product goals. You can have your respondents perform Forced-choice nature of the tasks, where in Survey Analytics MaxDiff can disentangle the relative feature importance in cases where average Likert-style ratings might all have very similar ratings.
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Max Diff Analysis - In Practice
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