CATEGORY APPRAISAL WITHIN A LIMITED PRODUCT RANGE: A METHODS-ORIENTED CASE HISTORY

This paper presents the author's approach to synthesizing useful direction from product testing when the stimuli are not systematically varied. The approach presented here comprises a research design and data analysis strategy, rather than a conventional product optimization with subsequent validation. The design steps comprise stimulus selection, attribute selection, and product evaluation. The data analysis comprises univariate modeling to show how sensory attributes drive overall liking, reduction of the matrix to factor scores for multivariate modeling, and then the creation of an integrated product model. The outcome is a set of factor scores that can be translated to sensory attributes and in turn to target products.     

IMPORTANCE OF SENSORY FACTORS IN PROCESSED SEAFOOD: METHODS AND RESULTS1

This paper considers “importance” of sensory attributes from the consumer point of view, with emphasis on processed seafood. There are three key measures of importance. Attitudinal importance measures what consumers think to be important and refers to general opinions about the category. Sensory system importance measures how strongly different sensory inputs (e.g., appearance, aroma, taste, texture) “drive” overall liking, and show the key sensory inputs to which consumers attend. Attribute level importance measures the relation between sensory intensity and overall liking for each attribute. It shows which specific attributes drive liking, how liking varies with the specific sensory attribute, and whether (and at what sensory level) there exists an optimal level.     

MARGARINE: THE DRIVERS OF LIKING AND IMAGE

This paper presents a study of the attributes of margarine, showing the depth of information about consumer perceptions and drivers of liking that emerges from a detailed analysis of relations among attributes. The paper develops three sets of analyses to understand relations among attributes: principal components analysis in order to identify basic dimensions of perception, linear functions relating overall liking to attribute liking or to image ratings in order to identify drivers of liking, and quadratic functions that relate overall liking or image ratings to sensory attribute levels in order to identify optimal sensory levels and to create sensory preference segments. The analyses show how consumer data can generate learning about the consumer perceptions on the one hand, and guidance for product development.     

USING HIGH-LEVEL CONSUMER-RESEARCH METHODS TO CREATE A TOOL-DRIVEN GUIDEBOOK AND DATABASE FOR PRODUCT DEVELOPMENT AND MARKETING

We present aspects and data for a tool‐driven database for marketing and product development, which are publicly accessible. The objective is to create a method whereby knowledge of concepts and products can be archived using overviews of a specific product category. The first phase of the database comprises systematic analysis of product concepts, which contain elements dealing both with features and emotions. The concept phase provides an idea about responses to statements about product features, along with responses to emotional elements and brands. The second phase comprises an analysis of the competitive frame of products, even before systematic product development is initiated. This second phase identifies expected and thus reasonable ranges of product‐sensory features, levels of acceptance of typical products, relations between liking and sensory attributes and segmentation of sensory preferences. Together, the two phases provide a guide to product developers new in a category, archive current knowledge and provide a sourcebook for marketers and developers alike, which is accessible using research tools. The two phases allow product development to become more scientific, more based on common experience rather than individual expertise and thus more efficient, without compromising corporate knowledge of specific ingredients, processes or business opportunities.     

COMPARISON OF ATTRIBUTE LIKING AND JAR SCALES TO EVALUATE THE ADEQUACY OF SENSORY ATTRIBUTES OF MILK DESSERTS

Just-about-right (JAR) scales and attribute liking questions are usually used to study consumer perception of the sensory characteristics of food products. The aim of the present work was to compare the performance of attribute liking and JAR scales to evaluate consumers' perceived adequacy of flavor and texture of milk puddings. Two groups of consumers were asked to evaluate eight milk desserts using (1) overall liking followed by attribute liking for texture and flavor and (2) overall liking followed by JAR scales for thickness, creaminess, sweetness and vanilla flavor. Overall liking scores were significantly different when JAR scales or attribute liking questions were considered. Texture, flavor and overall liking scores were highly correlated to each other, providing the same information. JAR scales correlated better with the intensity of sensory attributes evaluated by a trained sensory panel, being JAR percentages a reliable tool to study the adequacy of sensory attributes.

PRACTICAL APPLICATIONS

Results from the present work showed that consumers might not be able to independently evaluate their liking of different sensory attributes of a product. For this reason, the use of attribute liking questions for studying the adequacy of sensory attributes in complex products would not be recommended. JAR scales were better indicators of the adequacy of sensory attributes. Consumers were able to independently evaluate texture and flavor attributes using JAR scales. However, the influence of JAR scales on overall liking scores should be taken into account when including these scales on consumer studies.     

SELECTING PRODUCTS FOR CATEGORY APPRAISAL STUDIES — FEWER PRODUCTS DO ALMOST AS WELL AS MANY PRODUCTS

This paper analyzes the results of different strategies for selecting test products in category appraisals. The three strategies are random selection of products from the marketplace, selection on the basis of consumer sensory data, and selection on the basis of expert panel data. All three methods generate stable results for category appraisals. The stability of the results (e.g., in terms of 'drivers of liking') increases very quickly and then levels off, suggesting that the researcher does not have to work with a particularly large number of products in a category appraisal to understand the sensory-liking dynamics.
It appears in our case, that 18 products were an appropriate number to strongly reflect results for 50 products. Researchers need to be sensitive to the variation in each category. Some categories may require more or less than this number of products to cover all the sensory ranges within the specific category.     

A THURSTONE-COOMBS MODEL OF CONCURRENT RATINGS WITH SENSORY AND LIKING DIMENSIONS

A popular product testing procedure is to obtain sensory intensity and liking ratings from the same consumers. Consumers are instructed to attend to the sensory attribute, such as sweetness, when generating their liking response. We propose a new model of this concurrent ratings task that conjoins a unidimensional Thurstonian model of the ratings on the sensory dimension with a probabilistic version of Coombs' (1964) unfolding model for the liking dimension. The model assumes that the sensory characteristic of the product has a normal distribution over consumers. An individual consumer selects a sensory rating by comparing the perceived value on the sensory dimension to a set of criteria that partitions the axis into intervals. Each value on the rating scale is associated with a unique interval. To rate liking, the consumer imagines an ideal product, then computes the discrepancy or distance between the product as perceived by the consumer and this imagined ideal. A set of criteria are constructed on this discrepancy dimension that partition the axis into intervals. Each interval is associated with a unique liking rating. The ideal product is assumed to have a univariate normal distribution over consumers on the sensory attribute evaluated. The model is shown to account for 94.2% of the variance in a set of sample data and to fit this data significantly better than a bivariate normal model of the data (concurrent ratings, Thurstonian scaling, Coombs' unfolding model, sensory and liking ratings).     

EVALUATION OF BITTERNESS OF CAFFEINE IN HOT CHOCOLATE DRINK BY CATEGORY, GRAPHIC, AND RATIO SCALING

Perceived intensity of bitterness of caffeine (0.5 - 1.6 g/100 mL) and of quinine HCI (0.5 - 1.6 g/L) added to hot cocoa gave similar response distributions with concentration by category scales (CS) and magnitude estimation (ME). Using caffeine additives, CS and graphic analogue scales (GS) gave similar bitterness response functions. Parabolic functions provided the best fit between concentration and ratings for CS, GS and ME. The data demonstrated no difference for ME of bitterness intensity between free or fixed moduli. Hedonic responses also were not modified by whether the modulus was free or fixed, however, greater ME values were ascribed to lower concentrations in the series when the reference was 4 g/L than when it was 2 g/L caffeine. CS intensity response distributions were similar between a series with a larger number of low levels versus a series with a larger number of high levels across the same concentration range. The results indicate that ME may be inappropriate for scaling of degree of liking, independent of type of modulus.     

SENSORY PROPERTIES AND CONSUMER PERCEPTION OF 'HOME-MADE'AND COMMERCIAL DAIRY ICE CREAM

Sensory properties and consumer perception of 2 'home-made'and 4 commercial dairy ice creams were examined. Conventional profiling by a trained panel found that most samples differed significantly in all attributes, but distinction of 'home-made'from commercial products was limited to few attributes. Principal component analysis separated the 'home-made'products from the commercial ones mainly on the basis of differences in appearance, aroma, creamy flavors and textural attributes. A consumer group (n=105) recorded preconception of 'home-made'ice cream acceptance, then received the product samples, in unlabeled condition, for assessment of degree of liking (DOL) and for identification as 'home-made'or commercial. Internal preference mapping of the DOL ratings showed that consumers were more closely grouped around samples which had higher intensities of certain attributes. Higher 'denseness', 'vanilla'aroma and 'buttery'flavor, were associated with more liking for commercial products. The 'home-made'high fat sample, although liked, tended to be grouped with commercial products. More marked textural attributes of 'ice crystals'and 'breakage'aided identification of the low-fat 'home-made'formulation, which was less liked overall. Overall, differences between the 'home-made'and commercial samples were small but consumer perception of the term 'home-made'was viewed favorably for dairy ice cream.     

CONSUMER ACCEPTANCE OF COMMERCIALLY AVAILABLE FRANKFURTERS1

Consumers want meat products that are healthful and affordable. However, consumers will repurchase a product only if it tastes good. Consumers identified reasons for purchasing frankfurters and evaluated overall acceptability of 10 commercially available frankfurters. Consumers listed “taste” as the most important factor when purchasing frankfurters; only 16% of the consumers indicated that nutrition/health was the most important criterion. Nineteen consumer-perceived sensory and liking attributes were measured for the frankfurters in this study. The intensities of the attributes ranged from low to moderately high. All the frankfurters scored in the low to moderate range for overall acceptability. Most of the scores for liking of individual attributes correlated highly with overall liking, indicating that many of the questions relating to attribute liking could be eliminated.     

THE RELATION BETWEEN SENSORY, LIKING AND IMAGE ATTRIBUTES: THE CASE OF SOAP

This paper discusses the relation for soaps between sensory attributes and both liking and image attributes. A clear relation emerges between sensory attribute level and liking, but no clear relation emerges between sensory attributes and image attributes. There are two possible conclusions to be drawn from these results. One conclusion is that consumers can validly assign ratings to the image attribute of a soap, but that there is no way to trace this image rating back to sensory inputs. This conclusion suggests that more research is needed to understand the meaning of image attributes. The second conclusion is that consumers cannot validly rate the image attributes of a soap, even though they can complete the questionnaire. This second conclusion implies that consumers can validly rate some attributes (e.g., sensory, liking), but not others (e.g., image), and that it may be misleading to collect and attempt to analyze image ratings for health and beauty aids products.     

THE RELATIONSHIP BETWEEN CONSUMER PREFERENCES AND TRAINED PANEL RESPONSES

Eight samples of dried tomato soups were profiled by a trained panel, who also provided ratings of overall liking and liking for particular attributes on relative-to-ideal rating scales. A consumer panel tested a subset of four of the soups in home trials, assessing them for overall liking and for particular attributes on either hedonic or relative-to-ideal rating scales. The pattern of overall preferences differed between the trained and untrained panelists, demonstrating the inappropriateness of using trained panelists to provide measures of preference or acceptance. The conclusions regarding consumer preferences would differ depending on which rating scale was used; these differences disappeared when the relative-to-ideal ratings were converted into values of the same form as the hedonic ratings. The overall liking was best predicted by flavor rather than color or thickness. A principal components analysis (PCA) of the profile data compared well with a plot based on the trained panel preference data using MDPREF. The preference data were also fitted to the PCA dimensions using the PREMAP vector model, which gave a good fit for only six of the 15 trained panelists; the PREMAP ideal point model failed to show a better fit. In order to test these models adequately more than eight samples would need to be tested.     

INTERRELATIONS AMONG LIKING ATTRIBUTES FOR APPLE PIE: RESEARCH APPROACHES AND PRAGMATIC VIEWPOINTS

Liking is a key measure for applied product development. All too often, however, the liking attributes are simply reported, but other than analyzing overall liking ratings no other analysis is done on the ratings. Much more remains for applied product testers to learn from these liking attributes. This paper presents a detailed analysis of the interrelations among different liking attributes for apple pie. It shows that panelists discriminate among samples using different liking scales, but many of these scales correlate with each other creating a great deal of redundancy in the list of attributes. Factor analysis reveals one major dimension for liking of the entire pie, and three dimensions for liking of slices. A different way of analysis shows potentially more utility for developers. A linear model relating overall liking to each attribute liking reveals different slopes, suggesting different importance levels for the attribute liking scales. Furthermore, one can create an integrated liking model. The liking ratings can be combined into a single, overall product model, allowing the researcher to understand how changes in one liking attribute simultaneously affect all other liking attributes.     

QUESTIONNAIRE PRACTICE: WHAT HAPPENS WHEN THE JAR SCALE IS PLACED BETWEEN TWO “OVERALL” ACCEPTANCE SCALES?

ABSTRACT

Using the observational analysis of two different foods as test products, this note examined some interesting findings that emerge when the just‐about‐right (JAR) scale was placed after the overall liking rating, and before the preference ranking. The JAR data appeared to be statistically uncorrelated with the overall rating scales. First, this fortuitous observation from several studies suggests that the JAR scale can play a diagnostic role to determine how the consumer feels about changing the product. Second, the statistical analysis of the JAR ratings (e.g., bipolar nature of the JAR scale, its skewness and kurtosis) all suggest that the appropriate measure is %JAR, an incidence metric, rather than scale average, ought to be used both to report the results, and to create models relating to the JAR versus sensory magnitude or versus liking, respectively.

PRACTICAL APPLICATIONS

The results of the present analysis suggest that overall acceptance/liking can be the last question in the questionnaire design. That location is very important for the sensory analysis of foods eaten over time and then rated, as well as personal care and cosmetic studies where the products are used over time periods, and where the true evaluation of performance ought to be made at the end of the trial. In these long‐term uses, overall liking is generally the last question given at the end of the time period of product evaluation. The facts that the just‐about‐right (JAR) scales are independent of this final overall liking rating suggest that the integrity of the overall evaluation and usefulness of JAR as diagnostics will not be compromised.