Artificial empathy in marketing interactions: Bridging the human-AI gap in affective and social customer experience

Abstract

Artificial intelligence (AI) continues to transform firm-customer interactions. However, current AI marketing agents are often perceived as cold and uncaring and can be poor substitutes for human-based interactions. Addressing this issue, this article argues that artificial empathy needs to become an important design consideration in the next generation of AI marketing applications. Drawing from research in diverse disciplines, we develop a systematic framework for integrating artificial empathy into AI-enabled marketing interactions. We elaborate on the key components of artificial empathy and how each component can be implemented in AI marketing agents. We further explicate and test how artificial empathy generates value for both customers and firms by bridging the AI-human gap in affective and social customer experience. Recognizing that artificial empathy may not always be desirable or relevant, we identify the requirements for artificial empathy to create value and deduce situations where it is unnecessary and, in some cases, harmful.

It's all part of the customer journey: The impact of augmented reality, chatbots, and social media on the body image and self‐esteem of Generation Z female consumers

“…Augmented reality is defined as a “medium in which digital information is overlaid on the physical world that is in both spatial and temporal registration with the physical world and that is interactive in time” (Craig, 2013; p. 20). From a marketing perspective, two of the main benefits of chatbots enabled by artificial intelligence are powerful personalization and the option to automate services offered to customers (Ameen et al, 2022; Chandra et al, 2022; Liu‐Thompkins et al, 2022; Mariani et al, 2022). Chatbots have been defined as “an e‐service agent that represents a technological evolution of the traditional service agent involved in direct firm–customer exchanges” (Murtarelli et al, 2020; p. 2).…”

“…20). From a marketing perspective, two of the main benefits of chatbots enabled by artificial intelligence are powerful personalization and the option to automate services offered to customers (Ameen et al, 2022;Chandra et al, 2022;Liu-Thompkins et al, 2022;Mariani et al, 2022).…”

The development of Kondratieff’s theory of long waves: the place of the AI economy humanization in the ‘competencies-innovations-markets’ model

“…The performed in-depth context analysis of the existing literature has shown that large attention is paid to the issue of the social consequence of the transition to the AI economy. Liu-Thompkins et al (2022) substantiate the existence of artificial empathy in marketing interactions and the need to bridge the human-AI gap in affective and social customer experience. Lew and Walther (2022) assess the international practice of communication between humans or chatbots and AI and determine social scripts and expectancy violations.…”

Treating customers as individuals in online retail

“…The current study revealed that Russian consumers are already deeply embedded in the CX individualization . The trend towards CX individualization is visible in the recent events for practitioners (e .g ., [Client Service Forum, 2022]), in online retailers' practice (e .g ., Ozon or L'Etoile), and academic research [Hoyer et al ., 2020;Liu-Thompkins et al ., 2022] . One can assume that this trend represents an answer to an earlier call to go away from using discounts as the only way to create value and fight for the customer facing decreasing consumer income [Nielsen, 2018] .…”

“…11] . Interaction humanization implies that a firm empathetically react to customer inquiries, which can be realized through the combination of human and digital solutions that allow understanding the emotions of potential and real customers [Kulikova, Suvorova, 2022;Liu-Thompkins et al ., 2022] . One of the most popular technology-enabled ways to humanize customer-firm interaction is through cognitive and empathetic chatbots [Kozoriz, 2019;Behera, Bala, Ray, 2021;Agarwal, Maiya, Aggarwal, 2021] .…”