Consumers can be clustered based on their product-related check-all-that-apply (CATA) responses. We identify two paradoxes that can occur if these clusters are derived from conventional similarity coefficients. The first paradox is that clustering similar consumers can nullify within-cluster sensory differentiation of products. The second paradox is that consumers who check many attributes yet disagree can be clustered together, whereas consumers
Castura, J.C. (2021). Consumer hedonic studies with incomplete block designs. In: Workshop: A journey of consumer segmentation. History and a discussion of current “preference” segmentation approaches based on incomplete and complete test designs (Zach, J., Rothman, L., Carr, B.T., Thomas, H., Castura, J.C.). 14th Pangborn Sensory Science Symposium, 9-12 August. Online. (Workshop Oral). DOWNLOAD
A retail simulation study for investigating product choice and choice satisfaction: A case study involving kombucha
Kombucha is a fermented tea that is rapidly growing in popularity in the United States. As part of a larger consumer study conducted in Portland, Oregon, kombucha consumers (n=1303, 68% female, aged 18-86, USA)participated in an online retail simulation test. They evaluated 9 commercial products (bottle images) and made choice selections in a retail simulation.
Ralph Waldo Emerson once cautioned that “a foolish consistency is the hobgoblin of little minds.” In this talk, this quote is playfully considered in light of consumer diversity as manifested in sensory evaluation studies.
Sensory discrimination test methods are widely used by industry to guide decision-making. Interpretation increasingly relies on Thurstonian-derived models, which use mathematics to encode psychological decision-making rules, and map method-dependent results onto a putative method-independent discriminable distance (d′). It is also possible to estimate the response bias, or tau (τ), in some test methods, such as the same-different test method. Rousseau
Over the last decade, so-called rapid methods for sensory evaluation have been developed to permit consumers to characterize products. The possibility to analyze both sensory perception data and hedonic and other data arising from the same consumers presents new opportunities, but also new challenges to investigate hedonic drivers and other interesting aspects.
For the check-all-that-apply (CATA) question format, it is good practice to vary the attribute list order between evaluations to account for possible (and likely) position bias in the data. If attribute lists are to be randomized, the question is how to allocate these attribute lists orders.
Best practice recommendations for attribute order in Check-All-That-Apply (CATA) and related test methodologies
It is well documented that the position of attributes in a Check-All-That-Apply (CATA) question can bias responses. As positional biases cannot be eliminated, they are balanced across products via experimental designs, ensuring each attribute appears with equal frequency in each position for each product. But what is the best way to allocate attribute list orders?
Studies that investigate drivers of consumer liking involve both descriptive sensory and consumer data collection. These two components can be run in parallel to reduce project time, but at significant expense.
Check-all-that-apply (CATA) questionnaires have seen a widespread use recently. In this paper, we briefly review some of the existing approaches to analyze data obtained from such a study. Proposed extensions to these methods include a generalization of Cochran’s Q to test for product differences across all attributes, and a more informative penalty analysis.