MaxDiff Research

Maximum Difference Scaling (commonly referred to as MaxDiff) leverages a choice-task question methodology, whereby, for example, respondents select their most and least preferred product attribute from repeated choice sets. Choice sets are presented in a strategic matter, according to a balanced design whereby all features and enhancements appear in choice sets an equal number of times (usually at least three times). Survey Analytics's MaxDiff analysis can be applied to numerous research scenarios beyond product attribute preference and importance scoring, including product re-design and enhancements research, product line contraction analysis, and even as a platform for employee engagement studies, whereby employees to choose among aspects of their job they would most like and least like to change.

Survey Analytics Max Diff Analysis


MaxDiff 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.
  • Unlimited Attributes
  • Random Sub-Selection and Rotation
  • Utility / Share of Preference Calculation

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Max Diff Analysis - In Practice


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