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Custom Product Testing Techniques
Monadic Research Design
Monadic testing typically is the best method. Testing a product alone offers many advantages. Interaction between products (which occurs in paired-comparison tests)
is eliminated. The monadic test simulates real life (that's the way we usually use products, one at a time). By focusing the respondent's attention upon one product,
the monadic test provides the most accurate and actionable diagnostic information. Additionally, the monadic design permits the use of normative data and the development
of norms and action standards.
Virtually all products can be tested monadically, whereas many products cannot be accurately tested in paired-comparison designs. For example, a product with
a very strong flavor (hot peppers, alcohol, etc.) may deaden or inhibit the taste buds so that the respondent cannot really taste the second product.
Sequential Monadic Research Design
Sequential monadic designs are often used to reduce costs. In this design, each respondent evaluates two products (he or she uses one product and
evaluates it, then uses the second product and evaluates it). The sequential monadic design works reasonably well in most instances, and offers some of the
same advantages as pure monadic testing.
One must be aware of what we call the "suppression effect" in sequential monadic testing, however. All the test scores will be lower in a sequential
monadic design, compared to a pure monadic test. Therefore, the results from sequential monadic tests cannot be compared to results from monadic tests.
Also, as in paired-comparison testing, an "interaction effect" is at work in sequential monadic designs. If one of the two products is exceptionally good,
then the other product's test scores are disproportionately lower, and vice versa.
Protomonadic Research Design
The protomonadic design (the definition of this term varies greatly from researcher
to researcher) begins as a monadic test, followed by a paired-comparison. Often
sequential monadic tests are also followed by a paired-comparison test. The
protomonadic design yields good diagnostic data, and the paired-comparison test
at the end can be thought of as a safety net—as added insurance that the
results are correct. The protomonadic design is typically used in central-location
taste testing, not in home use test (because of the complexity of execution
in the home).
Paired-Comparison Test
Paired-comparison designs (in which the consumer is asked to use two products
and determine which product is better) appeal to our common sense. The paired-comparison
is a wonderful design if presenting evidence to a jury, because of its "face
value" or "face validity." It can be a very sensitive testing technique (i.e.,
it can measure very small differences) between two products. Also the paired-comparison
test is often less expensive than other methods, because sample sizes can be
smaller in some instances.
Paired-comparison testing, however, is limited in value for a serious, ongoing product-testing program. The paired-comparison test does not tell us when both
products are bad and does not lend itself to the use of normative data. It is heavily influenced by the "interaction effect" (i.e., any variations in the
control product will create corresponding variance in the test product's scores).
Repeated Pairs Test
A repeated paired-comparison taste test is exactly what the name suggests. Each respondent participates in a paired-comparison taste test (e.g., product J
versus product H), followed by a second paired-comparison test (product J versus product H). However, in the second test, the products are presented as
two different products (i.e., not labeled as products J and H).
The purpose of the repeated paired-comparison taste test is to identify nondiscriminators, the people who don't choose the same product in
both tests. That is, it is assumed that someone who chooses product J in the first paired-comparison test and chooses product H in the second
paired-comparison test cannot taste (or detect) any difference between the two products. Typically, these nondiscriminators' answers would not be counted. The
final results would be based only on respondents who could discriminate between the two products (i.e., based only on those who chose the same product both times).
Triangle Test
The triangle taste test is used primarily for "difference testing." Each participant is presented with three products and asked to taste all three
and choose the one that is different from the other two. The triangle taste test is used to determine who can discriminate (i.e., consistently identify the
one product that's different), and who cannot.
These discriminators are in turn used as members of small expert panels (sometimes called sensory panels) to assist research and development in formulating and
reformulating products, using the triangle design to determine if a particular ingredient change, or a change in processing, creates a detectable difference in the
final product. Triangle taste testing is also used in quality control to determine if a particular production run (or production from different factories) meets the
quality-control standard (i.e., is not different from the product standard in a triangle taste test using discriminators).
Sensory Research
The term "sensory research" tends to be used by research and development scientists and food scientists in much the same way that the marketing world
uses the term "product testing." Many of the methods are identical or very similar. In general usage, the term "sensory research" tends to refer to
small-scale product testing that is used by research and development scientists to help them in formulating new foods and beverages, and in reformulating
existing food and beverage products.
Often sensory research is conducted with small panels of consumers, or small groups of employees, who have demonstrated an above-average ability to
taste, or to detect, small differences in the flavor profile of a food or beverage.
Ingredient Screening
As a preliminary step in attempting to optimize a particular food or beverage formulation, it is valuable to develop an understanding of the relative
importance and role of the different ingredients in the formulation. Typically, a number of product formulations are created, each with a high level and a low
level (or absence) of a particular ingredient, with all other ingredients held constant. Each respondent usually rates three to five of these different
products, depending upon the type of product.
The products are rated on overall appeal as well as specific attributes (sweetness, texture, mouth feel, etc.). Who tastes which product is determined by
a complex experimental design plan. The resulting data are analyzed via ANOVA and MANOVA statistical techniques, as well as regression and discriminant
analyses. Choice-modeling and response-surface methods are also used.
Product Optimization
Product optimization refers to the process of improving a product until it reaches a maximum level of consumer satisfaction or acceptability. A variety of
research methods can be used to achieve an optimal product, but the term "product optimization" most typically refers to a structured process in which
various ingredients are systematically varied to create a number of different products.
These products are then rated by a sample of category users, with each respondent rating three to five different formulations on overall appeal as well as rating
specific qualities (moistness, saltiness, color, etc.) of the products. The resulting data is then analyzed by ANOVA and MANOVA, regression and discriminant analyses,
and (depending upon the design) by response-surface analyses or choice-modeling methods. The output of the analyses is a prediction of the product formulation that would be optimal.
Product Testing Services
Decision Analyst is a recognized leader in consumer product testing and optimization. Its staff has evaluated more than 1,000 foods, beverages, and other products
during the past 32 years. The firm has over 50 staff members with extensive experience in the conduct and analysis of product test and optimization studies. The company is
a leader in the development of analytical techniques to enhance product testing and optimization. If you would like more information on product
testing, please contact Jerry W. Thomas by emailing jthomas@decisionanalyst.com
or calling 1-800-ANALYSIS (262-5974) or 1-817-640-6166.
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