Quantitative Descriptive Analysis In Sensory Assessment

A girl licking an ice-cream. Quantitative Descriptive Analysis (QDA) is one way of being objective about the sensory profile of this type of product. A typical food emulsion.
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The analysis of sensory data is quite a straightforward process and in that armoury of assessment is Quantitative Descriptive Analysis. What follows is a short essay on the topic and how it helps the sensory analyst develop a profile of an ingredient or product.

It is always assumed that the higher the product quality the greater the drive towards consumer acceptance and an improvement in demand. Product quality needs to be measured somehow and this often takes the form of an assessment of the sensory quality, the sensory attributes that characterise a product. Knowing the sensory attributes of a product help the developer improve or tailor the offering so that the consumer’s expectations are not only met but possibly exceeded.

Over many years, a technique called quantitative descriptive profiling (QDA) has gained acceptability as the method for sensory evaluation (Stone et al., 2008). It’s been applied to many food products and the method is well represented throughout the sensory research literature. The principle of QDA is based on training panelists to measure certain specific attributes of a product in a reproducible way to yield a comprehensive quantitative product description which is then suitable for statistical analyses. The key attributes of a product are usually described by a series of words which must be complete so that all the important sensory properties are identified.

In the QDA approach, the panelists are usually recruited from the general public. They work together as a team in a focus group to identify the key product attributes and then produce an appropriate intensity Scale that is specific to a particular product. This group of panelists has to be trained to reliably identify and score on various product attributes. As panelists generate the attribute terms, the resulting descriptions are made meaningful to consumers, and so, such analyses provide information amenable to modelling predictions of consumer acceptability. QDA results can be analysed statistically and then represented graphically.

The most appropriate statistical method for analysing QDA data is Principal Component Analysis (PCA) which is a well tried and tested multivariate analytical statistical technique. It reduces the set of dependent variables termed the attributes, to a smaller set of underlying variables called factors. These factors are based on patterns of correlation among the original variables (Lawless and Heymann, 1998). The resulting data can then be applied to the following: (1) profiling specific product characteristics; (2) comparing and contrasting similar products based on attributes important to consumers; (3) and altering product characteristics with the goal of increasing market share for a given set of products.

QDA And Product Positioning

QDA has many valuable applications but one particular benefit is with product positioning. The technique can generate high quality descriptive sensory information which is then analysed as part of the critical steps in product development. Data also helps marketing groups assess the current situation with consumer products and then produce a well-defined competitive marketing strategy underpinned by statistical method.

Customers are targeted by improved product positioning because marketing teams can help the purchaser understand and appreciate the characteristics of their specific product in relation to those offered by competitors. In this strategy, each brand within a set of competitive products is thought to occupy a certain position in a customer’s “perceptual space” (Urban et al., 1987).

In general, marketing has two broad objectives in mind when undertaking perceptual mapping. One objective is to determine where a target brand is positioned versus the competition. The other objective is to help identify determinant product attributes that influence customer choice within the product class (Kohli and Leuthesser, 1993). These determinant attributes must be important to customers and must also exhibit differences across brands. Regardless of the importance of a product attribute, if brands are not perceived to differ in that attribute, then it will not be influential in customers’ decisions. Perceptual mapping might be the way forward to strategic product positioning for developing and marketing new conceptual products.

References

Kohli, C. S., and L. Leuthesser. 1993. Product positioning: a comparison of perceptual mapping techniques. J. Prod. Brand Mgt. 2 pp. 10–19.

Lawless, H. T., and Heymann. H. (1998) In:  Sensory Evaluation of Food: Principles and Practices. Chapman & Hall, New York, NY. pp. 606–608

Stone, H., and Sidel, J.L. 1998. Quantitative descriptive analysis: developments, applications, and the future. Food Technol. J. 52 pp. 48–52.

Stone, H., Sidel, J., Oliver, S., Woolsey, A. and Singleton, R.C., (2008) Sensory evaluation by quantitative descriptive analysis. In: Descriptive Sensory Analysis in Practice, pp.23-34.

Urban, G. L., J. R. Hauser, J.R., Dholakia., N. (1987) Mapping consumers’ product perception. in Essentials of New Product Management. Prentice-Hall, Englewood Cliffs, NJ. pp. 103–120

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