杠杆(统计)
业务
客户参与度
营销
客户保留
知识管理
客户情报
客户关系管理
首次公开发行
客户宣传
客户对客户
利润(经济学)
订单(交换)
计算机科学
人工智能
服务质量
社会化媒体
经济
服务(商务)
万维网
微观经济学
财务
作者
Tatiana Khvatova,Francesco Paolo Appio,Subhasis Ray,Francesco Schiavone
标识
DOI:10.1109/tem.2023.3284532
摘要
Artificial intelligence (AI) is becoming a pervasive technology and companies are increasingly urged to adopt and implement it in order to thrive and innovate. While much has been researched on the role AI can play in business-to customer (B2C) settings, a research gap exists when it comes to business-to-business (B2B), which is characterized by higher complexity, increasing number of players, and larger volumes of data. In such a context, an emerging issue deals with the possibility of understanding how companies can leverage AI to aptly manage the customer journey. This aspect touches on many organizational activities, so managers must be aware of existing solutions, process implications, and potential outcomes. In this article, we present an empirical study of 61 Indian B2B companies and provide an input-process-output (IPO) framework to help managers understand and profit from AI solutions while effectively managing the customer journey. We add value to literature on using AI to improve the customer journey in B2B settings. The developed IPO model can be used as a roadmap for introducing AI in managing customer journeys as well as a strategic instrument for organizational change and design.
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