Free Choice Profiling

 

Descriptive Analysis uses highly trained panelists to objectively assess product characteristics. They do not provide liking or acceptance responses and are usually treated as an instrumental measure. When testing with consumers, they are most frequently asked to rate specific attributes according to their liking or intensity (among other tests, but this article focuses on these two methods). These pre-determined attributes may not be important or detectable to the consumer and may not provide the necessary data¹.

 

Free-choice profiling (FCP) is a quick and inexpensive method in which consumers are asked to both identify attributes in the sample and rate the liking and/or intensity of those attributes². They should be provided with adequate instruction on how to perform this test and possibly given product categories to consider (aroma, appearance, flavor, texture, etc.). Each consumer will have different attributes, indicating which are most important. Though consumers should be recruited as normal (product usage, age/gender specifications), researchers may be able to separate consumers into groups, better identifying which characteristics are most important in that segment.

 

 

Since consumers will have developed different lexicons/vocabularies, similar terms may be grouped at the researcher’s discretion: first by category, then by term. It is important to note that consumers may use terms in different ways.

 

Generalized Procrustes Analysis (GPA) is a common statistical tool to analyze FCP data. GPA can compare FCP results across all terms. Values remain as individual data, not mean values. Results will indicate significant attributes, product discrimination and panelist performance³. Principal Component Analysis (PCA) on product attributes may also be used to graphically represent product and panelist scores, though not as clearly as GPA.

 

 

This method is quick, inexpensive and provides insight into consumer perception not given by a descriptive panel or traditional consumer testing. They may be suitable to marketing promotions, provide a new direction for product development or uncover unidentified product defects or considerations. However, terms generated by consumers may be too personal or difficult to interpret.

 

¹ Deliza, R, MacFie, H and Hedderley, D. 2005. The consumer sensory perception of passion-fruit juice using free-choice profiling. Journal of Sensory Studies, 20, 17-27.

 

² González-Viñas, MA, Garrido, N and Wittig de Penna, E. 2001. Free choice profiling of Chilean goat cheese. Journal of Sensory Studies, 16, 239-248.

 

³ Meullenet, JF, Xiong, R, and Findlay, C. 2007. Multivariate and Probabilistic Analyses of Sensory Science Problems. Iowa: Blackwell Publishing Professional.