Chatbot advertising effectiveness: When does the message get through?

By E. V. D. Broeck, Brahim Zarouali, Karolien Poels. 2019

226 citations recorded by the source corpus.

Abstract Chatbots on social networking sites are a recent innovation in computer-mediated marketing communication. In this study, 245 Facebook users between 18 and 35 years of age (Mage = 25.97, SD = 4.92) were asked to order tickets for the movies through Cinebot, a Facebook chatbot specifically built for the study. Afterwards, they were asked to evaluate their experiences via an online survey. The first purpose of this article was to investigate whether and how perceived helpfulness and usefulness of a chatbot consulted on the Facebook Messenger platform affected perceived intrusiveness of chatbot-initiated advertising in a later stage. In a second analysis, the relation between perceived intrusiveness and patronage intentions (i.e. purchase and recommendation intention of the product) was investigated. In addition, the role of message acceptance as a mediator and perceived message relevance as a moderator in this latter model were explored. As, to the best of our knowledge, our study is the first to investigate chatbot advertising, our research findings may hold important managerial implications.

Subfields: Information Systems and Management, Marketing, Sociology and Political Science, Human-Computer Interaction, Social Sciences & Humanities

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Citations in the corpus

Ethical and social risks of harm from Language Models (2021, background): “…and Sundar (2012) 2.5.3 Create avenues for exploiting user trust to obtain private information Ischen et al. (2019); Lewis et al. (2017); Van den Broeck et al. (2019) 2.5.4 Promoting harmful stereotypes by implying gender or ethnic identity Cercas Curry et al. (2020); Hwang et al. (2019);…”
Taxonomy of Risks posed by Language Models (2022, background): “In customer service chatbots, users more often accepted “intrusiveness” from chatbots that were perceived to be more helpful and useful [183], suggesting that”
Artificial intelligence in supply chain management: A systematic literature review (2021, background): “Chatbots on social networking platforms and websites represent a new innovation in computer-based marketing communication (Van den Broeck et al., 2019).”