Unveiling the dynamics of customer experience with AI-powered chatbots in online retail: a neuroscientific study
Ellen Roemer et al.
Abstract
Purpose A promising application of artificial intelligence (AI) in online retail is the implementation of AI-powered chatbots. However, online retailers must ensure that AI-powered chatbots enrich the customer experience during the customer journey while minimizing negative impacts. Therefore, this paper aims to investigate how an AI-powered chatbot influences the affective and the cognitive component of customer experience across different stages of the customer journey. Design/methodology/approach Using neuroscience tools, the authors use a mixed-design experiment to assess affective and cognitive customer experience in an online shop. The study compares two groups – one using an AI chatbot with one using the standard website (control group) – across customer journey stages. In particular, electrodermal activity (EDA) was measured to assess arousal as an indicator of the affective component, while eye-tracking was used to assess attention as an indicator of the cognitive component of customer experience. In this way, the study provides neuroscientific insights into the dynamics of two components of customer experience across different stages of the customer journey. Findings Based on the EDA metrics, the tested AI chatbot did not have a significant impact on the dynamics of participants’ arousal (affective component) throughout the customer journey stages compared to the control group. Nevertheless, the study revealed increasing peak arousal in the purchase stage for both groups generally indicating the emotional importance of this stage in the customer journey. Regarding the cognitive component, participants who used the chatbot developed higher levels of attention, and thus greater cognitive engagement, throughout the customer journey compared to the control group, as indicated by two eye-tracking metrics. Practical implications The findings offer implications for online retailers, brands, consultants, IT specialists and UX designers. To improve the affective experience, AI chatbots should offer emotional reassurance during the purchase stage and incorporate playful elements. Due to the increasing attention levels (cognitive experience), they should be trained to provide high-quality information that is customized to cater for individual informational needs and tailored to each customer journey stage, e.g. offering suitable product alternatives in the prepurchase stage and clarifying transactional information in the purchase stage. They should incorporate supportive visual or audio features to reduce cognitive load in crucial customer journey stages. Originality/value This paper substantially contributes to the literature by offering fundamentally new neuroscientific insights into the dynamics of customer experience by simultaneously assessing the affective and cognitive customer experience with a real AI-powered chatbot across the customer journey. It explores two components of the customer experience at the same time instead of focusing on one component. In addition, it takes an innovative methodological approach combining neuroscientific tools measuring EDA and eye movements. The neuroscientific insights reveal the dynamics of the components of customer experience throughout the prepurchase and purchase stage of the customer journey.
1 citation
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.16 × 0.4 = 0.06 |
| M · momentum | 0.53 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.