Research On The Impact Of Customer Experience With AI Products On Customer Behavioural Engagement

While the development of artificial intelligence(AI)products such as smart cars and smart speakers is on the rise,there is a relative lack of literature on the customer experience with AI products,especially in terms of quantitative research(which may be attributed to the fact that scales related to the experience of AI products have not yet been developed).In practice,we also often see problems with AI products in terms of customer experience due to poor performance leading to poor customer engagement,such as the goal of AI technology developers to achieve technical excellence that may conflict with the goal of marketers to provide a good customer experience,and price fraud due to intelligent dynamic pricing.Algorithms are often described by computer scientists as neutral tools judged by efficiency and accuracy,while it may ignore the complexity of the AI application environment,where consumers are often exposed to algorithmic pitfalls that lead to a deteriorating customer experience.Therefore,it is of strong theoretical and practical significance to conduct research on the customer experience of AI products based on the customer perspective.Therefore,based on Assemblage theory,this paper explores the composition of customer experience with AI products and its impact on customer behavioural engagement through two studies: "Scale development of customer experience with AI products" and "Study on the impact of customer experience with AI products on customer behavioural engagement".Study 1: Scale development for customer experience with AI products.Based on Puntoni’s(2021)research on customer experience with AI dimensions,the “customer experience with AI products scale” was developed using the Grounded theory coding method.(2)Open coding and spindle coding of text data,combined with Puntoni’s(2021)research results to form conceptual dimensions and indicators;(3)exploratory and validation factor analysis(valid sample size of 296 and 239 respectively)to form dimensions and measurement indicators of customer experience with AI products,specifically,the scale includes “Classification Experience”,“Delegation Experience”,“Anthropomorphic Experience” and “Social Experience”,with 14 indicators.Study 2: The impact of customer experience with AI products on customer behavioural engagement.This study has three research objectives: firstly,to investigate the impact of customer experience with AI products on customer behavioural engagement,secondly,to investigate the mediating mechanism of its impact,and thirdly,to investigate the moderating effect of personal innovativeness.The data for Study 2 was obtained through a questionnaire survey with a total sample of 239 respondents.The research method used was mainly multiple linear regression.The findings of the study revealed that:(1)customer experience with AI products helps to enhance customers’ behavioural engagement with the company or brand.Specifically,there was a significant positive relationship between classification experience,delegation experience,anthropomorphic experience and social experience in customer experience with AI products and customer behavioural engagement.(2)Self-extension partially mediates the impact of customer experience with AI products on customer behavioural engagement.(3)Personal innovativeness moderates the effect of customer experience with AI products on self-extension and customer behavioural engagement,specifically,the increase of personal innovativeness weakens the positive effect of customer experience with AI products on self-extension and customer behavioural engagement.This paper is innovative in the following aspects: first,based on Puntoni’s(2021)study,customer experience with AI products scale was developed to provide scale support for further related research.Secondly,the basic argument put forward by Brodie(2011)in the context of AI technology is empirically tested,namely that customer engagement arises in the context of a specific service relationship by virtue of an interactive customer experience with an object.This provides a useful complement to Brodie’s(2011)proposal to ’explore the fundamental nature of the interactive engagement experience in different contexts’.Thirdly,the study finds that self-extension can partially explain the influence mechanism of customer experience with AI products on customer behavioural engagement,and empirically examines the moderating effect of the individual customer characteristic of personal innovativeness on the relevant influence path from the perspective of individual customer heterogeneity,which is a powerful addition to the relatively scarce research on consumer behaviour in the context of AI.Finally,based on the findings,the paper proposes marketing recommendations on how companies(or brands)should design or enhance the customer experience with AI products to strengthen customer engagement.