Next-Generation Consumer Innovation Search: Identifying Early-Stage Need-Solution Pairs on the Web
37 Pages Posted: 28 Oct 2018 Last revised: 11 Jul 2019
Date Written: July 1, 2019
All completed innovations inherently contain information about both a need and a responsive solution – they are “need-solution pairs”. Today, technical advances in machine-learning techniques for natural language understanding, such as semantic word space models and semantic network analytics, have made it practical to capture descriptions of early-stage, need-solution pairs mentioned anywhere in the open, textual content of the Internet. This is important because, often, both the need and the responsive solution in consumer-developed innovations are novel and pioneering.
Conventional marketing research methods are not able to identify functionally novel needs embedded in such user-developed innovations at such an early stage of development and diffusion, as they are at that stage generally known to too few and their potential impact is as yet unseen. It is therefore our claim that a next-generation, broad internet search to identify and screen all novel consumer-developed need-solution pairs will enable a broader discovery of potentially valuable innovation opportunities and future market directions. The new internet search method we will describe can serve as a complement to traditional market research techniques and practices. In this paper, we first explain our reasoning and methodological approach in detail. Next, we demonstrate, via a case study in the household sector, both the practicality and the value of searching for early-stage need-solution pairs via the semantic word space and network analytic methods we describe. Finally, we discuss the research and practical implications of this new approach.
Keywords: problem-solving; need-solution pairs; user innovation; consumer innovation; household sector innovation
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