Online vehicle sales : use cases for intelligent virtual agents along the customer journey in the automotive industry - Bleicher, Selina Maresa (2022)
Artificial intelligence (AI) comes in multiple forms and is rapidly disrupting various businesses and industries. While OEMs are demonstrating their ability to innovate and use artificial intelligence in areas such as smart mobility, production improvements, and logistics, there is still a lack of innovative technology use in the automotive customer journey. Consequently, the traditional vehicle purchase is frequently perceived as outdated and inferior, especially among younger customers. In this context, the strategic use of intelligent virtual agents (IVA) at different customer touchpoints represents a promising opportunity to strive for a superior customer experience. The aim of this paper is to present use cases for IVAs along the customer journey in the automotive industry and to prioritise them according to their usage potential. To obtain a holistic view, the assessment is made from two perspectives: that of the customer by the online survey and that of the company by expert interviews. Based on this analysis, key enablers and bottlenecks for a successful deployment of intelligent virtual agents are obtained. The findings revealed that IVA use cases functioning as recommendation systems in the vehicle configuration phase achieve the greatest priority among the use cases presented. Moreover, there are strong synergies between three cases that together represent a tremendous pool of value: product recommendation, scheduling appointments, and transfer to human agent. To leverage the full potential of IVAs, OEMs and dealers are encouraged to create a heterogeneous data ecosystem with a particular emphasis on data security to enable a seamless customer journey.