Beyond interaction: Generative AI in conversational marketing - foundations, developments, and future directions
Abstract views: 1070 / PDF downloads: 844
DOI:
https://doi.org/10.15637/jlecon.2294Keywords:
AI in marketing, Conversational Marketing, Digital Marketing, Generative AI, Customer EngagementAbstract
This paper explores the integration of Generative Artificial Intelligence (AI) in conversational marketing, transitioning from traditional marketing to interactive, customer-centric strategies. It examines the shift from one-way communication to dynamic, AI-driven interactions that personalize customer experiences. Central to this study is how Generative AI facilitates real-time, tailored dialogues between brands and customers, enhancing customer engagement and satisfaction. The paper also addresses the challenges and ethical considerations of using anthropomorphic AI in marketing, balancing human-like AI traits with user expectations. Additionally, it presents a novel framework that conceptualizes the combination of Generative AI and anthropomorphism in conversational marketing into four distinct quadrants, providing a comprehensive analysis of their potential interplay. Conclusively, it offers strategic insights for leveraging AI in marketing while adhering to ethical practices, highlighting the potential of Generative AI to transform customer engagement in the digital age. This research has two important consequences. Practically, it offers valuable insights and strategic recommendations for businesses aiming to integrate Generative AI into their conversational marketing practices effectively. Theoretically, it contributes to the academic discourse by highlighting the transformative role of Generative AI in marketing, suggesting avenues for future research in this rapidly evolving field. This study provides a brief overview of the evolving role of AI in modern marketing strategies, emphasizing the future potential and implications of AI-driven conversational marketing.
Downloads
References
ALAN, M. (1950). Turing. Computing machinery and intelligence. Mind. 59(236), 433-460.
BABAYEV, N. and ISRAFILZADE, K. (2023) “Creating complexity matrix for classifying artificial intelligence applications in e-commerce: New perspectives on value creation”, JOURNAL OF LIFE ECONOMICS. 10(3), 141–156. doi: 10.15637/jlecon.2078
BECERIK-GERBER, B., LUCAS, G., ARYAL, A., AWADA, M., BERGES, M., BILLINGTON, S. L., ... & ZHAO, J. (2022). Ten questions concerning human-building interaction research for improving the quality of life. Building and Environment. 226, 109681.
BUDHWAR, P., CHOWDHURY, S., WOOD, G., AGUINIS, H., BAMBER, G. J., BELTRAN, J. R., ... & VARMA, A. (2023). Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT. Human Resource Management Journal. 33(3), 606-659.
CAMBRIDGE ENGLISH DICTIONARY (2023). Conversation. CONVERSATION | meaning in the Cambridge English Dictionary. https://dictionary.cambridge.org/dictionary/english/conversation?q=Conversation.
CANCEL, D., GERHARDT, D., & DEVANEY, E. (2019). Conversational marketing: How the world's fastest growing companies use chatbots to generate leads 24/7/365 (and how you can too). Hoboken, NJ: Wiley.
CHANDRA, S., SHIRISH, A., & SRIVASTAVA, S. C. (2022). To be or not to be… human? Theorizing the role of human-like competencies in conversational artificial intelligence agents. Journal of Management Information Systems. 39(4), 969-1005.
CHENG, Y. & JIANG, H. (2021) 'Customer–brand relationship in the era of artificial intelligence: understanding the role of chatbot marketing efforts,' Journal of Product & Brand Management. 31(2), 252–264. https://doi.org/10.1108/jpbm-05-2020-2907.
CIECHANOWSKI, L., PRZEGALINSKA, A., MAGNUSKI, M., & Gloor, P. (2019). In the shades of the uncanny valley: An experimental study of human–chatbot interaction. Future Generation Computer Systems, 92, 539-548.
CROLIC, C., THOMAZ, F., HADI, R., & STEPHEN, A. T. (2022). Blame the bot: Anthropomorphism and anger in customer–chatbot interactions. Journal of Marketing, 86(1), 132-148.
DHANDAYUTHAPANI, V. B. (2022). A Proposed Cognitive Framework Model for a Student Support Chatbot in a Higher Education Institution. International Journal of Advanced Networking and Applications. 14(2), 5390-5395.
DWIVEDI, Y. K., KSHETRI, N., HUGHES, L., SLADE, E. L., JEYARAJ, A., KAR, A. K., ... & WRIGHT, R. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management. 71, 102642.
EINHORN, M. and LÖFFLER, M. (2021) 'Transformation of customer insights,' in Emerald Publishing Limited eBooks. 5–18. https://doi.org/10.1108/978-1-83909-694-520211002.
EPLEY, N., WAYTZ, A., & CACIOPPO, J. T. (2007). On seeing human: a three-factor theory of anthropomorphism. Psychological review. 114(4), 864.
FERNANDEZ, R. A. S., SANCHEZ-LOPEZ, J. L., SAMPEDRO, C., BAVLE, H., MOLINA, M., & CAMPOY, P. (2016). Natural user interfaces for human-drone multi-modal interaction. In 2016 International Conference on Unmanned Aircraft Systems (ICUAS). 1013-1022. IEEE.
FITZPATRICK, G. (2018). A short history of human computer interaction: A people-centred perspective. In Proceedings of the 2018 ACM SIGUCCS Annual Conference. 3-3.
FØLSTAD, A., & BRANDTZÆG, P. B. (2017). Chatbots and the new world of HCI. Interactions. 24(4), 38-42.
FØLSTAD, A., NORDHEIM, C. B., & BJØRKLI, C. A. (2018). What makes users trust a chatbot for customer service? An exploratory interview study. In International Conference on Internet Science. 194-208. Springer, Cham.
GAETANO, S., & DILIBERTO, P. (2018). Chatbots and conversational interfaces: Three domains of use. In Fifth International Workshop on Cultures of Participation in the Digital Age, Castiglione della Pescaia, Italy. 2101, 62-70..
GOODFELLOW, I., POUGET-ABADIE, J., MIRZA, M., XU, B., WARDE-FARLEY, D., OZAIR, S., ... & BENGIO, Y. (2014). Generative adversarial nets. Advances in neural information processing systems. 27.
GRUDIN, J. (2022). From tool to partner: The evolution of human-computer interaction. Springer Nature.
GUTHRIE, S. E. (1995). Faces in the clouds: A new theory of religion. Oxford University Press.
HARBOLA, A. (2021). Design and implementation of an AI chatbot for customer service. The Philippine Statistician (Quezon City). 70(2), 1295–1303. https://doi.org/10.17762/msea.v70i2.2321
HORI, C., PEREZ, J., HIGASHINAKA, R., HORI, T., BOUREAU, Y., INABA, M., . . . KIM, S. (2019). Overview of the sixth dialog system technology challenge: DSTC6. Computer Speech & Language. 55, 1-25. doi:10.1016/j.csl.2018.09.004
HOROWITZ, A. C., & BEKOFF, M. (2007). Naturalizing anthropomorphism: Behavioral prompts to our humanizing of animals. Anthrozoös. 20(1), 23-35.
HOUDE, S., LIAO, V., MARTINO, J., MULLER, M., PIORKOWSKI, D., RICHARDS, J., ... & ZHANG, Y. (2020). Business (mis) use cases of generative ai. arXiv preprint arXiv:2003.07679.
HU, Y., & SUN, Y. (2023). Understanding the joint effects of internal and external anthropomorphic cues of intelligent customer service bot on user satisfaction. Data and Information Management. 7(3), 100047.
HUSSAIN, S., AMERI SIANAKI, O., & ABABNEH, N. (2019). A Survey on Conversational Agents/Chatbots Classification and Design Techniques. In L. Barolli, M. Takizawa, F. Xhafa, & T. Enokido (Eds.), Advances in Intelligent Systems and Computing. Web, Artificial Intelligence and Network Applications (Vol. 927, pp. 946–956). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-15035-8_93
ISRAFILZADE, K. (2020). What’s in a name? Experiment on the aesthetic judgments of art produced by artificial intelligence. Journal of Arts. 3(2), 143-158. https://doi.org/10.31566/arts.3.011
ISRAFILZADE, K. (2021) 'Conversational marketing as a framework for interaction with the customer: Development & validation of the conversational agent’s usage scale,' Journal of Life Economics. 8(4), 533–546. https://doi.org/10.15637/jlecon.8.4.12
ISRAFILZADE, K. (2023a). Beyond Automation: The Impact of Anthropomorphic Generative Ai on Conversational Marketing. 8th INTERNATIONAL EUROPEAN CONFERENCE ON INTERDISCIPLINARY SCIENTIFIC RESEARCH. 5(2), 757–766. https://doi.org/10.5281/zenodo.8253308
ISRAFILZADE, K. (2023b). The Role of Generative AI and Anthropomorphism in Shaping Conversational Marketing: Creating a Matrix for Future Research. The Eurasia Proceedings of Educational and Social Sciences, 32.
JAKESCH, M., FRENCH, M., MA, X., HANCOCK, J. T., & NAAMAN, M. (2019, May). AI-mediated communication: How the perception that profile text was written by AI affects trustworthiness. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. 1-13.
JAMIL, M. B. A., & SHAHZADI, D. (2023). A systematic review A Conversational interface agent for the export business acceleration. Lahore Garrison University Research Journal of Computer Science and Information Technology. 7(2), 37-49.
KACZOROWSKA–SPYCHALSKA, D. (2019) 'How chatbots influence marketing,' Management. 23(1), 251–270. https://doi.org/10.2478/manment-2019-0015.
KOCABALLI, A. B., LARANJO, L., & COIERA, E. (2019). Understanding and measuring user experience in conversational interfaces. Interacting with Computers. 31(2), 192-207.
LİU, X., ZHENG, Y., DU, Z., DİNG, M., QİAN, Y., YANG, Z., & TANG, J. (2023). GPT understands, too. AI Open.
MAKANY, T., ROH, S., HARA, K., HUA, J. M., GOH Sİ YİNG, F., & TEH YANG JİE, W. (2023). Beyond Anthropomorphism: Unraveling the True Priorities of Chatbot Usage in SMEs. In Proceedings of the 5th International Conference on Conversational User Interfaces. 1-5
MAULDIN, M. L. (1994). Chatterbots, tinymuds, and the turing test: Entering the loebner prize competition. In AAAI. 94, 16-21.
MCCARTHY, J., MINSKY, M. L., & ROCHESTER, N. (1956). The Dartmouth summer research project on artificial intelligence. Artificial intelligence: past, present, and future.
MOORE, R. J., ARAR, R., REN, G. J., & SZYMANSKI, M. H. (2017). Conversational UX design. In Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems. 492-497.
MURPHY, J., GRETZEL, U., & PESONEN, J. (2019). Marketing robot services in hospitality and tourism: the role of anthropomorphism. Journal of Travel & Tourism Marketing. 36(7), 784-795.
NURUZZAMAN, M., & HUSSAIN, O. K. (2018). A Survey on Chatbot Implementation in Customer Service Industry through Deep Neural Networks. https://doi.org/10.1109/icebe.2018.00019
OOİ, K. B., TAN, G. W. H., AL-EMRAN, M., AL-SHARAFİ, M. A., CAPATİNA, A., CHAKRABORTY, A., ... & WONG, L. W. (2023). The potential of Generative Artificial Intelligence across disciplines: perspectives and future directions. Journal of Computer Information Systems. 1-32.
PAGANI, M., RACAT, M. & HOFACKER, C.F. (2019) 'Adding Voice to the Omnichannel and How that Affects Brand Trust,' Journal of Interactive Marketing. 48, 89–105. https://doi.org/10.1016/j.intmar.2019.05.002.
PILELIENĖ, L. & JUCEVIČIUS, G., (2023). A Decade of Innovation Ecosystem Development: Bibliometric Review of Scopus Database. Sustainability. 15(23), 1-26.
PİLELİENĖ, L., ALSHARİF, A. H., & ALHARBİ, I. B. (2022). Scientometric analysis of scientific literature on neuromarketing tools in advertising. Baltic Journal of Economic Studies. 8(5), 1-12.
PRZEGALINSKA, A., CIECHANOWSKI, L., STROZ, A., GLOOR, P., & MAZUREK, G. (2019). In bot we trust: A new methodology of chatbot performance measures. Business Horizons. 62(6), 785–797. https://doi.org/10.1016/j.bushor.2019.08.005
RADFORD, A., WU, J., CHILD, R., LUAN, D., AMODEI, D., & SUTSKEVER, I. (2019). Language models are unsupervised multitask learners. OpenAI blog. 1(8), 9.
RĖKLAITIS, K., & PILELIENĖ, L. (2019). Principle differences between B2B and B2C marketing communication processes. Organizacijø Vadyba: Sisteminiai Tyrimai. (81), 73-86.
RHEU, M. et al. (2020) 'Systematic Review: Trust-Building Factors and Implications for Conversational Agent Design,' International Journal of Human-Computer Interaction. 37(1), 81–96. https://doi.org/10.1080/10447318.2020.1807710.
SEARLE, J. R. (1980). Minds, brains, and programs. 417-457.
SHEEHAN, B., JIN, H. S., & GOTTLIEB, U. (2020). Customer service chatbots: Anthropomorphism and adoption. Journal of Business Research. 115, 14-24
SHUMANOV, M., & JOHNSON, L. W. (2021). Making conversations with chatbots more personalized. Computers in Human Behavior. 117, 106627. https://doi.org/10.1016/j.chb.2020.106627
SINHA, S., & SINGH, T. (2018). Travel from Traditional Marketing to Digital Marketing. International Journal of Emerging Research in Management and Technology, 6(11), 173. https://doi.org/10.23956/ijermt.v6i11.60
SOTOLONGO, N., & COPULSKY, J. (2018). Conversational marketing: Creating compelling customer connections. Applied Marketing Analytics. 4(1), 6-21.
WAN, E. W., & CHEN, R. P. (2021). Anthropomorphism and object attachment. Current Opinion in Psychology. 39, 88-93.
WANG, X., & YUAN, C. (2016). Recent Advances on Human-Computer Dialogue. CAAI Transactions on Intelligence Technology. 1(4), 303-312. doi:10.1016/j.trit.2016.12.004
WEIZENBAUM, J. (1966). ELIZA—a computer program for the study of natural language communication between man and machine. Communications of the ACM. 9(1), 36-45.
WEIZENBAUM, J., & MCCARTHY, J. (1977). Computer Power and Human Reason: From Judgment to Calculation. Physics Today. 30(1), 68-71. doi:10.1063/1.3037375
WIGDOR, D., & WIXON, D. (2011). Brave NUI world: Designing natural user interfaces for touch and gesture. Amsterdam: Elsevier/Morgan Kaufmann.
XU, W. (2019). Toward human-centered AI: a perspective from human-computer interaction. Interactions. 26(4), 42-46.
ZADROZNY, W., BUDZIKOWSKA, M., CHAI, J., KAMBHATLA, N., LEVESQUE, S., & NICOLOV, N. (2000). Natural language dialogue for personalized interaction. Communications of the ACM. 43(8), 116-120.
ZHANG, S., DINAN, E., URBANEK, J., SZLAM, A., KIELA, D., & WESTON, J. (2018). Personalizing Dialogue Agents: I have a dog, do you have pets too? https://doi.org/10.18653/v1/p18-1205
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 JOURNAL OF LIFE ECONOMICS
This work is licensed under a Creative Commons Attribution 4.0 International License.
When the article is accepted for publication in the Journal of Life Economics, authors transfer all copyright in the article to the Holistence Publications.The authors reserve all proprietary right other than copyright, such as patent rights.
Everyone who is listed as an author in this article should have made a substantial, direct, intellectual contribution to the work and should take public responsibility for it.
This paper contains works that have not previously published or not under consideration for publication in other journals.