2 MIN READ | Cognitive Psychology

How Computer Scientists and Marketers Can Create a Better CX With AI, According to New Research

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, (2020, October 28). How Computer Scientists and Marketers Can Create a Better CX With AI, According to New Research. Psychreg on Cognitive Psychology. https://www.psychreg.org/computer-scientists-marketers-ai/
Reading Time: 2 minutes

Researchers from Erasmus University, The Ohio State University, York University, and London Business School published a new paper in the Journal of Marketing that examines the tension between AI’s benefits and costs and then offers recommendations to guide managers and scholars investigating these challenges.

The study, forthcoming in the Journal of Marketing, is titled ‘Consumers and Artificial Intelligence: An Experiential Perspective’ and is authored by Stefano Puntoni, Rebecca Walker Reczek, Markus Giesler, and Simona Botti.

Not long ago, artificial intelligence (AI) was the stuff of science fiction. Now it is changing how consumers eat, sleep, work, play, and even date. Consumers can interact with AI throughout the day, from Fitbit’s fitness tracker and Alibaba’s Tmall Genie smart speaker to Google Photo’s editing suggestions and Spotify’s music playlists. Given the growing ubiquity of AI in consumers’ lives, marketers operate in organisations with a culture increasingly shaped by computer science. Software developers’ objective of creating technical excellence, however, may not naturally align with marketers’ objective of creating valued consumer experiences. For example, computer scientists often characterise algorithms as neutral tools evaluated on efficiency and accuracy, an approach that may overlook the social and individual complexities of the contexts in which AI is increasingly deployed. Thus, whereas AI can improve consumers’ lives in very concrete and relevant ways, a failure to incorporate behavioural insight into technological developments may undermine consumers’ experiences with AI.

This article seeks to bridge these two perspectives. On one hand, the researchers acknowledge the benefits that AI can provide to consumers. On the other hand, they build on and integrate sociological and psychological scholarship to examine the costs consumers can experience in their interactions with AI. As Puntoni explains, ‘A key problem with optimistic celebrations that view AI’s alleged accuracy and efficiency as automatic promoters of democracy and human inclusion is their tendency to efface intersectional complexities.’

The article begins by presenting a framework that conceptualizes AI as an ecosystem with four capabilities: data capture, classification, delegation, and social. It focuses on the consumer experience of these capabilities, including the tensions felt. Reczek adds, ‘To articulate a customer-centric view of AI, we move attention away from the technology toward how the AI capabilities are experienced by consumers. Consumer experience relates to the interactions between the consumer and the company during the customer journey and encompasses multiple dimensions: emotional, cognitive, behavioural, sensorial, and social.’

The researchers then discuss the experience of these tensions at a macro level, by exposing relevant and often explosive narratives in the sociological context, and at the micro level, by illustrating them with real-life examples grounded in relevant psychological literature. Using these insights, the researchers provide marketers with recommendations regarding how to learn about and manage the tensions. Paralleling the joint emphasis on social and individual responses, they outline both the organisational learning in which firms should engage to lead the deployment of consumer AI and concrete steps to design improved consumer AI experiences. The article closes with a research agenda that cuts across the four consumer experiences and ideas for how researchers might contribute new knowledge on this important topic.


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