5 minutes to read. By author Michaela Mora on November 8, 2021 Topics: Analysis Techniques, Conjoint Analysis, New Product Development, Quantitative Research, Survey Design
Making the case for MaxDiff (Maximum Difference Scaling) is getting easier. MaxDiff provides greater advantages than rating, ranking, and allocation questions when we use it to research preferences and importance attribution,
First, let’s look at the question types that have been traditionally used to study preferences and what’s important to people.
It is rare these days, to find surveys without rating questions, despite the many problems associated with them. Rating questions are susceptible to:
Ranking questions are also common in surveys. Unfortunately, they also have many limitations. These include:
Although less common, constant sum questions are often used in an attempt to find greater discrimination. However, these questions have their own set of weaknesses, including:
The problems with each of these question types, particularly with rating questions, have led to an increased interest in the use of Maximum Difference Scaling or MaxDiff as is commonly called.
This is a trade-off analysis technique that allows us to do multiple pairwise comparisons in an effective way. We do it by repeatedly asking respondents to select the most and the least preferred or important items from a list.
In order to implement a MaxDiff study, we need to:
The standard output of MaxDiff analysis is usually a ranking of the items tested based on rescaled utilities.
Since MaxDiff yields ratio data, we can also conduct further multivariate analysis including TURF and segmentation analysis
We have used MaxDiff to study preferences for and importance of a number of things including, among others:
MaxDiff is better than the alternatives discussed above, but it is not perfect.
Although there are ways to calibrate the MaxDiff results to “absolute” levels of preference or importance, we always recommend doing preliminary research, ideally qualitative research, to make sure to include relevant items in the MaxDiff list.
Next time you need to measure preferences or importance consider using MaxDiff instead of traditional approaches such as rating, ranking, or constant sum questions.
You will gain data quality, greater discrimination, and the ability to provide better insights to support business decisions.
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