The future of marketing

Rust, Roland T.

doi:10.1016/j.ijresmar.2019.08.002

Cited by 232 publications

(139 citation statements)

References 45 publications

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“…For service organisations, the question is not whether to use AI but to what extent and how to maximise its capacity to improve the efficiency and effectiveness of the services that they provide (Huang anad Rust, 2018; Ostrom et al, 2019; Rust, 2019; Wirtz et al, 2018). Currently, AI is being utilised in such service industries as education, finance, health care, retailing, and transportation.…”

Section: Introductionmentioning

confidence: 99%

AI Customer Service: Task Complexity, Problem-Solving Ability, and Usage Intention

Shieh²,

Esch

et al. 2020

Australasian Marketing Journal

187

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Artificial intelligence (AI) in the context of customer service, we define as a technology-enabled system for evaluating real-time service scenarios using data collected from digital and/or physical sources in order to provide personalised recommendations, alternatives, and solutions to customers’ enquiries or problems, even very complex ones. We examined, in a banking services context, whether consumers preferred AI or Human online customer service applications using an experimental design across three field-based experiments. The results show that, in the case of low-complexity tasks, consumers considered the problem-solving ability of AI to be greater than that of human customer service and were more likely to use AI while, conversely, for high-complexity tasks, they viewed human customer service as superior and were more likely to use it than AI. Moreover, we found that perceived problem-solving ability mediated the effects of customers’ service usage intentions (i.e., their preference for AI vs. Human) with task complexity serving as a boundary condition. Here we discuss our research and the results and conclude by offering practical suggestions for banks seeking to reach customers and engage with them more effectively by leveraging the distinctive features of AI customer service.

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Section: Introductionmentioning

confidence: 99%

AI Customer Service: Task Complexity, Problem-Solving Ability, and Usage Intention

Shieh²,

Esch

et al. 2020

Australasian Marketing Journal

187

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show abstract

“…This wedge is critical, as revealing consumers' true motivations entail empathetic reasoning (e.g., Madsbjerg & Rasmussen, 2014). Moreover, the advent of a so‐called “feeling economy,” fueled by technological advances making the human capacity for empathy a competitive strength against artificial intelligence (AI), suggests that empathy should take an even more prominent role in the practice of marketing in the years to come (Ferràs‐Hernández, 2018; Huang et al, 2019; Rust, 2020b; Rust & Huang, forthcoming).…”

Section: Introductionmentioning

confidence: 99%

Empathy‐based marketing

Pedersen

2021

Psychology and Marketing

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Empathy, that is, the capacity of understanding another person's perspective and feelings, has conventionally been a pillar of marketing, as the discipline from its very inception has emphasized the importance of understanding and putting oneself in the shoes of customers. Yet, with an increasing focus on rationality, objectivity, and science, marketing has arguably become more empathy‐deprived. This is unfortunate, as the increasing objectification, specialization, and the resultant distancing and fragmentation of the marketing field make it proportionally essential to emphasize an empathetic approach to marketing. Here, I address this gap by (re)introducing an empathetic approach to marketing entitled empathy‐based marketing. Empathy‐based marketing addresses the increasing customer‐distancing and subdivision of the field of marketing, by focusing on an empathetic core, stimulating cross‐fertilization, and accentuating the general well‐being of the field. Beyond discussing what this paradigm is and why the field needs it, an agenda for future research is also outlined.

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“…However, these algorithms are far from using common sense reasoning in a way that is comparable to the human. There is a surprisingly long history of this type of research (see, e.g., [51][52][53]). However, the use of new approaches in artificial intelligence there is the likelihood of success in using verbal descriptions in marketing problems.…”

Section: Discussionmentioning

confidence: 99%

Fuzzy Similarity Used by Micro-Enterprises in Marketing Communication for Sustainable Development

Schüller

Doubravský

2019

Sustainability

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The purpose of this paper is to present fuzzy reasoning as a formal tool for determining the differences in perception of individual communication channels by customers. These differences in customer perception are important for micro-enterprises to develop an effective green advertising campaign. These kinds of enterprises are not able to conduct their own extensive marketing research or use the service of marketing agencies. Micro-enterprises are the cornerstone for sustainable local economic growth where the community plays an irreplaceable role for sustainable development. Marketing communication is unique and complex because it focuses on feelings, moods, and personal preferences. The main problem is the uncertainty of this input data which makes it difficult to develop effective green advertising campaigns. Fuzzy sets and fuzzy reasoning are used to make verbal descriptions suitable for computer applications. A fuzzy pairwise similarity is used in this paper. The case study has eight relevant variables/marketing communication media, e.g., e-mailing, social networks, web pages, text messaging, newspapers, phone calls, posters and radio, and five segments of respondents selected by age. Each segment is presented as a fuzzy conditional statement. A set of fuzzy pairwise similarities is generated.

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The future of marketing

Cited by 232 publications

References 45 publications

AI Customer Service: Task Complexity, Problem-Solving Ability, and Usage Intention

AI Customer Service: Task Complexity, Problem-Solving Ability, and Usage Intention

Empathy‐based marketing

Fuzzy Similarity Used by Micro-Enterprises in Marketing Communication for Sustainable Development

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