Predicting success for new flavors with information known pre-launch: a flavored snack food case study



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Success in the marketplace is the goal of every product launch. Knowing what data to collect before launching a product that could predict success would be valuable to companies. Thus, the objective of this study was to determine whether success of new line extensions for a multi-flavored snack product available internationally could be predicted from information available before launch. Staff from 15 countries completed a questionnaire for each product and included questions related to authenticity, familiarity, and capturing current trends, packaging and market place issues such as product competition and pricing. Using 63 flavors, a discriminant function correctly identified 75.8% successful products as successful and 66.7% unsuccessful products as unsuccessful. Stepwise comparison determined the variables necessary to correctly categorize the snack products: being a trendy flavor, new to the category, based off foods from restaurants or traditional foods. These variables assisted in predicting in market success for this product category.



Success, Discriminant analysis, Product development, Stepwise regression