Journal of Marketing · 2023 · 260 citations · 63 references
BusinessComputer ScienceMarketingArtificial IntelligenceCustomer Relationship ManagementRelationship MarketingAffective ComputingCustomer EngagementCustomer Experience ManagementCustomer SatisfactionEmotion RecognitionEmpathic RespondingAutomatic Emotion RecognitionCustomer Emotion AnalysisCustomer EmpathyCustomer Lifetime Value PredictionEmotion ElicitationEmotion Perception AccuracyEmotional Customer ExperienceInterpersonal Relationship Building
Customer care builds relationships, traditionally handled by humans, but emerging generative AI offers potential for emotionally charged interactions. The article develops an AI‑enabled customer‑care journey that moves from accurate emotion recognition to empathetic response, emotional‑management support, and ultimately an emotional connection. The authors derive marketing requirements from interviews and surveys, compare them with current GenAI capabilities to identify challenges, and propose solutions such as emotion‑recognition verification, prompt engineering, response engineering, and strategic deployment to enhance customer well‑being and lifetime value. The article concludes with marketing tenets for implementing and researching the caring machine.
Customer care is important for its role in relationship building. This role has traditionally been performed by human customer agents; however, the emergence of interactive generative AI (GenAI) shows potential for using AI for customer care in emotionally charged interactions. Bridging practice and the academic literatures in marketing and computer science, this article develops an AI-enabled customer care journey, from accurate emotion recognition to empathetic response, emotional management support, and, finally, the establishment of an emotional connection. Marketing requirements for each of the stages are derived from in-depth interviews with top managers and a survey of chief marketing officers. By juxtaposing these requirements against the current feeling capabilities of GenAI, the authors highlight the technological challenges engineers must tackle. The article concludes with a set of marketing tenets for implementing and researching the caring machine. These include verifying emotion recognition accuracy using marketing emotion theories through multiple emotion signals and methods, utilizing prompt engineering to enhance GenAI’s emotion understanding, employing “response engineering” to personalize emotion management recommendations, and strategically deploying GenAI for emotional connection to simultaneously enhance customer emotional well-being and customer lifetime value.
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Journal of the American Dietetic Association · 1994 · 46.5K citations
Artificial Intelligence in Service
Ming‐Hui Huang, Roland T. Rust · Journal of Service Research · 2018 · 3.3K citations
Management, Human Resource Management, Organizational Behavior +11