Example : Respondents are provided with a set of attributes from which they are asked to indicate which of them is most important (preferred) and which is least important (preferred). Respondents traditionally complete a series of approximately some sets. Each set is designed to show the respondent a different subset of items. Through careful survey design, all items and pairs of items are displayed an equal number of times. Additionally, each respondent will see a different set of choice models. However, each respondent will typically be offered each item at least two times across the exercise. The typical Max-Diff exercise includes 15 to 40 attributes to be measured. Responses are analyzed using techniques to derive attribute importance scores at the individual respondent level.
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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