Concept testing
Concept testing (to be distinguised from test marketing) is the process of using quantitative methods and - sometimes in the earlier stages -qualitative methods to evaluate consumer response to a product idea prior to the introduction of a product to the market. Some confuse concept testing (which traditionally refers to new-product concept testing) with communications research - such as advertising research and packaging research.
The concept generation stage of concept testing can take on many forms. Examples include technological advances, brain-storming sessions, and qualitative research. In the early stages, multiple-alternative new concepts might exist, requiring concept-screening surveys. Concept screening surveys provide little detail, and are mainly used to reduce the number of options, before moving on to concept-testing surveys, which provide greater detail and quantitative results.
There are many different approaches used in concept testing surveys, in terms of how new concepts are displayed. In brief:
1.) Monadic. The concept is evaluated in isolation. 2.) Sequential monadic. Multiple concepts are evaluated in sequence (often randomized order). 3.) Comparative. Concepts are shown next to each other. 4.) Proto-monadic. Concepts are first shown in sequence, and then next to each other.
Each has its specific uses and it depends on the research objectives of the study. This decision is best left to experience research professionals to decide, as their are numerous implications in terms of how the results are interpreted.
Evaluating concept-test scores
Traditionally concept-test survey results are compared to 'norms databases'. These are large databases of previous new-product concept tests. To be fair, it is important that these databases contain 'new' concept test results, not ratings of old products that consumers are already familiar with; since once consumers become familiar with a product the ratings often drop. Comparing new concept ratings to the ratings for an existing product already on the market would result in an invalid comparison, unless special precautions are taken by researchers to reduce or adjust for this effect quantitatively. Additionally, the concept is usually only compared to norms from the same product category, and the same country.
Other methods have also been developed that do not use norms databases for concept evaluation. At the end of the day, the specific approach matters less than applying standards consistently. Companies that specialise in this area, tend to have developed their own unique systems, each with its own internal standards.
One of the oldest concept-test systems is the Nielsen Bases system. Other examples include Decision Analyst, Accupoll, Ipsos, Eric Marder's Step Model, Acentric Express Test and many others.
Determining the importance of concept attributes as purchase drivers
The simplest approach to determining attribute importance is to ask direct open-ended questions. Alternatively checklists or ratings of the importance of each product attribute may be used.
However, various debates have existed over whether or not consumers could be trusted to directly indicate the level of importance of each product attribute. As a result, correlation analysis and various forms of multiple regression have often been used for identifying importance - as an alternative to direct questions.
A complementary technique to concept testing, is conjoint analysis (also referred to as discrete choice modelling). Various forms of conjoint analysis and discrete choice modelling exist. While academics stress the differences between the two, in practice there is often little difference. These techniques estimate the importance of product attributes indirectly, by creating alternative products according to an experimental design, and then using consumer responses to these alternatives (usually ratings of purchase likelihood or choices made between alternatives) to estimate importance. The results are often expressed in the form of a 'simulator' tool which allows clients to test alternative product configurations and pricing.
Volumetric concept testing
Volumetric concept testing falls somewhere between traditional concept testing and pre-test market models (simulated test market models are similar but emphasize greater realism) in terms of the level of complexity. The aim is to provide 'approximate' sales volume forecasts for the new concept prior to launch. They incorporate other variables beyond just the input from the concept test, such as marketing plans. Some models gather additional product testing survey (especially in the case of consumer packaged goods as repeat purchase rates need to be estimated), along with advertising test results - in which case they are more properly referred to as pre-test market models or simulated test markets.
See also
References
- Moore, William L. (1982). Concept Testing. Journal of Business Research 10, 279-294