89-9 |
A data analysis method to build a product idea knowledge base |
G. J. STUCKY, J. D. Kolsky, D. C. Plaehn, and D. S. Lundahl. CAMO Inc., PO Box 1628, Corvallis, OR 97339 Using historical data from one or more conjoint studies, knowledge bases can be built that define the many relationships between consumer and product concepts. These knowledge bases offer a better starting point to product developers to more clearly define the optimal product concept for a specific target market. This ensures that product development can more quickly focus activities to build new products that have a greater likelihood of success. This research shows how conjoint research data can be used to build a knowledge base and to use the knowledge base to generate optimal product ideas for a defined market segment. Unique partial least squares models with interactive terms were created for every respondent. Respondent models were aggregated into combined models for defined market segments. A market-share simulator was used to predict the top ten optimal product ideas from each of the combined models that would capture the largest market share. Filters were applied to incorporate user-defined information from the knowledge base. Results for these defined markets were compared and contrasted. Data from a conjoint study are discussed and compared to show the added benefit of utilizing an interactive knowledge base versus a standard conjoint analysis. An interactive knowledge base increases the value of the research data over a written static report. Researchers are able to create a better starting point for future research projects, and to achieve a base of valuable information accessible to a wider range of people.
Session 89, Product Development
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