Just about right (JAR) questions are used in consumer taste tests to provide feedback to product developers as to whether an attribute or ingredient in a product is at the ideal level or if it requires adjustment. The scale used for these questions is bipolar, with the first and last scale points representing too much or too little of an attribute, and the midpoint representing the “just about right” point.
Examples of typical JAR questions include:
• Rate the COLOR of this product: Much Too Light; Somewhat Too Light; Just About Right; Somewhat Too Dark; Much Too Dark.
• Rate the SWEETNESS of this product: Not Nearly Sweet Enough; Not Quite Sweet Enough; Just About Right; Somewhat Too Sweet; Much Too Sweet.
• Rate the AMOUNT OF SAUCE in this product: Not Nearly Enough; Somewhat Not Enough; Just About Right; Somewhat Too Much; Far Too Much.
When a 5-point scale is used, the results are typically collapsed into three categories: not enough, just about right and too much. JAR results are generally reported as three numbers per attribute. For example, reporting a result of 20/70/10 would be one way to show that 20% of the consumers thought the attribute intensity was too low or “not enough;” 10% thought it was too strong or “too much;” and 70% thought it was “just about right.” A general rule of thumb is that an attribute can be considered sufficiently optimized when at least 70% or 75% of the consumers marked the “just about right” option.
JARred advantages
JARs have been widely used in food industry research for at least two decades, for the following reasons:
JARS are easy to understand. JARs are easily comprehended, provided that the words used to anchor the scales are true semantic op-posites and the attributes are well understood by consumers. JARs are a simple way to gather information from a target population of consumers, and the results are relatively easy to communicate in presentations.
JARs shortcut the development process. Well-optimized products can be developed via experimental design, in which attribute levels or treatments are systematically varied and the resulting products tested with consumers, or by using key attribute drivers studies, in which several products representing a variety of product attributes and attribute levels are presented to consumers. From the data gathered in these studies, attributes of the target product can be predicted based on consumers’ liking of each product in the test set.
Although the studies described above remain the gold standard in product research using consumers, they are not always undertaken due to a greater up-front investment of time and money. JAR questions provide one means of shortcutting the product-development and consumer-testing process. Rather than making a sensory attribute an experimental factor in a study, JARs allow us to make an attribute a question on a questionnaire. The results can then be used to provide direction as to whether an attribute should be increased, decreased or left unchanged.
JARs can be used in tandem with liking (hedonic) questions to better understand which attributes have a large impact on consumer liking. This information can be used to prioritize which attributes should be adjusted.
Understanding the pitfalls
Although JARs are commonly included in consumer questionnaires, their use still creates some debate. One reason for this contro-versy is that JARs are often employed incorrectly or the resulting scores are interpreted in a too-literal fashion, which then leads the de-veloper astray and ultimately results in failure to improve the product.