Today's businesses face a high pressure to innovate in order to succeed in highly competitive markets. Successful innovations, though, typically require the identification and analysis of customer needs. While traditional, established need elicitation methods are time-proven and have demonstrated their capabilities to deliver valuable insights, they lack automation and scalability and, thus, are expensive and time-consuming. In this article, we propose an approach to automatically identify and quantify customer needs by utilizing a novel data source: Users voluntarily and publicly expose information about themselves via social media, as for instance Facebook or Twitter. These posts may contain valuable information about the needs, wants, and demands of their authors. We apply a Design Science Research (DSR) methodology to add design knowledge and artifacts for the digitalization of innovation processes, in particular to provide digital support for the elicitation of customer needs. We want to investigate whether automated, speedy, and scalable need elicitation from social media is feasible. We concentrate on Twitter as a data source and on e-mobility as an application domain. In a first design cycle we conceive, implement and evaluate a method to demonstrate the feasibility of identifying those social media posts that actually express customer needs. In a second cycle, we build on this artifact to additionally quantify the need information elicited, and prove its feasibility. Third, we integrate both developed methods into an end-user software artifact and test usability in an industrial use case. Thus, we add new methods for need elicitation to the body of knowledge, and introduce concrete tooling for innovation management in practice.
翻译:今天的企业面临巨大的创新压力,以在高度竞争性的市场上取得成功。但成功的创新通常需要识别和分析客户需求。虽然传统的、公认的需求激发方法是经过时间验证的,并表明其提供宝贵见解的能力,但它们缺乏自动化和可缩放性,因此成本昂贵和耗时。在本篇文章中,我们建议采用一种方法,通过使用新的数据来源自动识别和量化客户需求。用户自愿和公开通过社交媒体(例如Facebook或Twitter)披露自己的信息。这些职位可能包含关于作者需求、需求及需求的宝贵信息。我们采用设计科学研究(DSR)方法来增加创新进程数字化设计知识和工艺,特别是为客户需求的征求提供数字支持。我们要调查从社交媒体中自动、快速和可缩放需求是否可行。我们集中关注推特作为数据源和电子流动性作为应用域。在第一个设计周期中,我们设想、实施和评价一种方法,以显示识别这些社会媒体职位的可行性,以实际表达客户需求。我们需要的是,通过一个最终的测试周期,我们需要一种测试方法来构建一个最终的系统。我们需要一种最终的系统,我们需要一种最终的系统。