Maximizing overall liking results in a superior product to minimizing deviations from ideal ratings: An optimization case study with coffee-flavored milk

• Optimizing liking and minimizing dissatisfaction yield distinct product optimal formulations.
• Consumers may not know what they want but know what they like.
• Asking a consumer panel to design a product using JAR or ideal scales may be misleading.
• Optimizing liking is a reliable tool to create a preferable product.
• Both JAR and ideal scaling commit similar biases.

In just-about-right (JAR) scaling and ideal scaling, attribute delta (i.e., “Too Little” or “Too Much”) reflects a subject’s dissatisfaction level for an attribute relative to their hypothetical ideal. Dissatisfaction (attribute delta) is a different construct from consumer acceptability, operationalized as liking. Therefore, we hypothesized minimizing dissatisfaction and maximizing liking would yield different optimal formulations. The objective of this research was to compare product optimization strategies, i.e., maximizing liking vis-à-vis minimizing dissatisfaction.Coffee-flavored dairy beverages (n = 20) were formulated using a fractional mixture design that constrained the proportions of coffee extract, milk, sucrose, and water. Participants (n = 388) were randomly assigned to one of three research conditions, where they evaluated 4 of the 20 samples using an incomplete block design. Samples were rated for overall liking and for intensity of the attributes sweetness, milk flavor, thickness and coffee flavor. Where appropriate, measures of overall product quality (Ideal_Delta and JAR_Delta) were calculated as the sum of the absolute values of the four attribute deltas. Optimal formulations were estimated by: (a) maximizing liking; (b) minimizing Ideal_Delta; or (c) minimizing JAR_Delta. A validation study was conducted to evaluate product optimization models.Participants indicated a preference for a coffee-flavored dairy beverage with more coffee extract and less milk and sucrose in the dissatisfaction model compared to the formula obtained by maximizing liking. That is, when liking was optimized, participants generally liked a weaker, milkier and sweeter coffee-flavored dairy beverage. Predicted liking scores were validated in a subsequent experiment, and the optimal product formulated to maximize liking was significantly preferred to that formulated to minimize dissatisfaction by a paired preference test. These findings are consistent with the view that JAR and ideal scaling methods both suffer from attitudinal biases that are not present when liking is assessed. That is, consumers sincerely believe they want ‘dark, rich, hearty’ coffee when they do not. This paper also demonstrates the utility and efficiency of a lean experimental approach.