Taxonomic Free Sorting: A Successful Method with Older Consumers and a Novel Approach to Preference Mapping

Abstract

Taxonomic free sorting (TFS) is a fast, reliable and new technique in sensory science. The method extends the typical free sorting task where stimuli are grouped according to similarities, by asking respondents to combine their groups two at a time to produce a hierarchy. Previously, TFS has been used for the visual assessment of packaging whereas this study extends the range of potential uses of the technique to incorporate full sensory analysis by the target consumer, which, when combined with hedonic liking scores, was used to generate a novel preference map. Furthermore, to fully evaluate the efficacy of using the sorting method, the technique was evaluated with a healthy older adult consumer group. Participants sorted eight products into groups and described their reason at each stage as they combined those groups, producing a consumer-specific vocabulary. This vocabulary was combined with hedonic data from a separate group of older adults, to give the external preference map. Taxonomic sorting is a simple, fast and effective method for use with older adults, and its combination with liking data can yield a preference map constructed entirely from target consumer data. PRACTICAL APPLICATIONSGenerating diagnostic sensory data directly from target consumers is a challenge in sensory science. Taxonomic free sorting (TFS) is a new and efficient sorting technique that aims to determine the sensory characteristics of products that are important to specific consumer cohorts. The hierarchical stages of TFS gives a better indication of the similarities and differences of a sample set and in this study was combined with consumer hedonic data to generate a preference map. In this study the attributes of the products assessed were provided directly by older consumers, without the need for training or prompting. TFS is a quick and effective method to give clear guidance of positive and negative characteristics of products according to the target consumer, as well as involving the specific consumer audience throughout the testing process.

Exploring salient dimensions in a free sorting task: A cross-country study within the elderly population

“…Overall the results suggest that FST allowed the detection of differences in sample categorization in the different age groups of the elderly population and the different countries, and so is applicable for older adults. The present research therefore corroborates the good applicability of sorting methodology with healthy older adults as reported by Withers et al (2014).…”

Sound quality perception of loudspeakers evaluated by different sensory descriptive methods and preference mapping

“…When comparing to the classical approach some authors concluded that these methods give similar results to external preference mapping. Other applications using rapid methods can be found in Varela, Beltrán, and Fiszman (2014), using preference ranking and open comments in Withers et al (2014)), and using taxonomic free sorting and liking in Faye et al (2006) with focus on liking of textiles.…”

Influence of cluster analysis procedures on variation explained and consumer orientation in internal and external preference maps

“…Preference maps have been used extensively for many types of sensory marketing and product development studies for determining drivers of liking (Hwang & Hong, ; Jervis et al, ; Kim & Kim, ; Kim, Lee, Kwak, & Kang, ; Villamor, Daniels, Moore, & Ross, ; Withers et al, ), product quality and optimization (Delgado and Guinard, ; Lawless, Threlfall, Meullenet, & Howard, ; Mahanna & Lee, ; Neely, Lee, & Lee, ), and the introduction of new products into a blank space on a map (de Morais & Pereira ; Donadini & Fumi, ). Delgado and Guinard, , Zhang et al (), Leksrisompong, Lopetcharat, Guthrie, and Drake (), and Paulsen, Næs, Ueland, Rukke, and Hersleth () interpreted a preference map based only on its configuration.…”