Traditional preference testing is expensive with more than two products because of the large number of comparisons that require evaluation. Applicability scoring was originally used in product testing partly to develop an alternative method for deriving an analog preference measure in sequential monadic testing. Since the method is used sequentially, it can be used for more than two products. When the attribute is liking (the item scored is I like this product), the method allows the separation of like both from like neither which is not provided using a preference question with a no preference option. Therefore, this capability provides more information about the acceptability of both products than can be obtained from a preference test.
Applicability scoring requires the consumer to indicate whether each term or statement ‘applies’ or ‘does not apply’ to the sample evaluated. When it was first used in the sensory field and compared to traditional preference testing, it was found to be comparable in sensitivity.
In this technical report, we extend the learnings from our previous report to illustrate how applicability scoring can be a viable alternative to traditional preference or other paired comparison tests. We will show that theoretically it exhibits a similar statistical power to paired testing, supporting the original comparative testing, and can be executed far more cost-effectively using a sequential monadic design.
This technical report appears as:
Ennis, D. M. and Rousseau, B. (2018). Derived Preference from Applicability Scoring. IFPress, 21(3) 3-4.
Derived Preference from Applicability Scoring