Steps towards a consumer-driven concept innovation machine for 'ordinary' product categories in their later lifecycle stages
This paper presents a research-driven approach to innovating product features in categories considered to be mature and low involvement. The approach begins with the identification of product features realizable by developers, works with consumers using Internet research tools (conjoint analysis) to identify features that drive acceptance, and further identifies opportunities by both varying the respondent's task (rating on different end uses) and using concept-response segmentation to uncover new mind-sets. The actual identification of innovation opportunities emerges most clearly from the segmentation of respondents into like-minded clusters of individuals, with clearly different patterns of desired features. Within those clusters are seeds of new product ideas. The approach finishes with methods to identify significant interactions among product features which drive further opportunities, procedures to execute multiple parallel studies which stimulate additional thinking, and applications of rule-based genetic algorithms to mix/match winning elements from different products in order to create even newer ideas.
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