Maximum Difference Scaling is an approach for obtaining preference/importance scores for multiple items (brand preferences, brand images, product features, advertising claims, etc.). Although it shares much in common with conjoint analysis, it is easier to use and applicable to a wider variety of research situations. It is also known as "best-worst scaling".
Maximum Difference Scaling is a technique that allows marketers to identify the "best" of many alternatives- preferences in product features or benefits, marketing slogans, logos, service options, or something else entirely like names for a restaurant.
Maximum Difference Scaling sounds like it might be complex, but with Survey Analytics, this technique is actually straightforward.
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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