Voice Engagement Leading to Business Intelligence: A Systematic Review and Agenda for Future Research

Praveen Kumar Sattarapu, Deepti Wadera, Jaspreet Kaur
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Abstract

There are multiple studies establishing the importance of Business Intelligence (BI), in the Big Data Analytics context. Voice is yet to be seen as a contributing channel. Voice enabled assistants are at the forefront of conversational AI advancement. As humans speak to devices, brands and business are investing in engagement through voice channel. This voice engagement is resulting in both intangible and tangible benefits and generating voice commerce. The resultant voice data should be integral to BI, leading to Voice BI. This paper proposes a conceptual framework from engagement to intelligence, with support of five propositions to realise voice business intelligence. Type of applications and their engagement characterisation is segregated to create better understanding using Cross-Cases Observation Technique. Along with future research agenda to strengthen the propositions, this investigation observes building voice business intelligence by tracking relevant metrics which enable informed decisions.
语音参与导致商业智能:系统回顾和未来研究议程
在大数据分析的背景下,有多项研究确立了商业智能(BI)的重要性。Voice尚未被视为一个有贡献的渠道。语音助手是对话式人工智能发展的前沿。随着人类与设备对话,品牌和企业正在通过语音渠道投资于互动。这种语音参与产生了无形和有形的利益,并产生了语音商务。生成的语音数据应该是BI的组成部分,从而实现语音BI。本文提出了一个从参与到智能的概念框架,并提出了实现语音商业智能的五个主张。应用程序的类型和它们的参与特征是分开的,以便使用跨案例观察技术创建更好的理解。随着未来的研究议程,以加强主张,本调查观察通过跟踪相关指标,使明智的决策建立语音商业智能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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