Conversational marketing as a framework for interaction with the customer: Development & validation of the conversational agent's usage scale

Yıl 2021, Cilt: 8 Sayı: 4, 533 - 546, 31.10.2021

Khalil Israfılzade

Öz

Conversational agents are becoming an essential part of a growing number of personal and commercial encounters, bringing the issue of Conversational Marketing to a broader audience. A conversational agent is a developing technology that will be used in various fields throughout life, including e-commerce. The common characteristics of any conversational agent in whatever area are their capacity to engage in one-to-one personalised real-time dialogue with a human user and their availability 24 hours a day. Scale items for conversational agent phenomena have not been created scientifically or managerially in a business environment. The primary goal of this study was to develop and validate a new scale for conversational agents that could be used to quantify individual interactions in conversational marketing. As a result, the creation of a new scale for conversational agents with the objective of measuring individual customer interactions in conversational marketing was separated into two phases: Scale Development and Scale Validation. The Conversational Agent Usage Scale was developed and validated as a consequence of pilot studies. Additionally, this article discusses the practical consequences of conversational marketing, which can now be accomplished through the use of the Conversational Agent Usage Scale, which may be used by Customer Service & Support, Marketing, and Sales departments.

Anahtar Kelimeler

Conversational Marketing, Artificial Intelligence, Anthropomorphism, Human-Computer Interaction

Kaynakça

• ADAM, M., WESSEL, M., & BENLIAN, A. (2020). AI-based chatbots in customer service and their effects on user compliance. Electronic Markets, 1-19.
• AGUIRRE, E., ROGGEVEEN, A. L., Grewal, D., & Wetzels, M. (2016). The personalisation-privacy paradox: implications for new media. Journal of Consumer Marketing.
• AKERKAR, R. (2019). Artificial Intelligence for Business. SpringerBriefs in Business. doi:10.1007/978-3-319-97436-1
• ALMANSOR, E. H., & HUSSAIN, F. K. (2020). Survey on Intelligent Chatbots: State-of-the-Art and Future Research Directions. In L. Barolli, F. K. Hussain, & M. Ikeda (Eds.), Advances in Intelligent Systems and Computing. Complex, Intelligent, and Software Intensive Systems (Vol. 993, pp. 534–543). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-22354-0_47
• ASHFAQ, M., YUN, J., YU, S., & LOUREIRO, S. M. C. (2020). I, Chatbot: Modeling the determinants of users' satisfaction and continuance intention of AI-powered service agents. Telematics and Informatics, 54, 101473.
• ATIYAH, A., JUSOH, S., & ALMAJALI, S. (2018, July). An efficient search for context-based chatbots. In 2018 8th International Conference on Computer Science and Information Technology (CSIT) (pp. 125-130). IEEE.
• BANCHS, R. E. (2017, December). On the construction of more human-like chatbots: Affect and emotion analysis of movie dialogue data. In 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) (pp. 1364-1367). IEEE.
• BAVARESCO, R., SILVEIRA, D., REIS, E., BARBOSA, J., RIGHI, R., COSTA, C., ANTUNES, R., GOMES, M., Gatti, C., Vanzin, M. and Silva, E., (2020). Conversational agents in business: A systematic literature review and future research directions. Computer Science Review, 36, p.100239.
• BLUNCH, N. (2008). Introduction to Structural Equation Modelling Using SPSS and AMOS. doi:10.4135/9781446249345
• CALDER, B. J., ISAAC, M. S., & MALTHOUSE, E. C. (2016). How to capture consumer experiences: A context-specific approach to measuring engagement: Predicting consumer behavior across qualitatively different experiences. Journal of Advertising Research, 56(1), 39-52.
• CAMBRIDGE ENGLISH DICTIONARY (2020). 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.
• CHUNG, M., Ko, E., JOUNG, H. and KIM, S.J., (2020). Chatbot e-service and customer satisfaction regarding luxury brands. Journal of Business Research, 117, pp.587-595.
• CHURCHILL Jr, G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of marketing research, 16(1), 64-73.
• 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. https://doi.org/10.1016/j.future.2018.01.055
• CUI, L., HUANG, S., WEI, F., TAN, C., DUAN, C., & ZHOU, M. (2017, July). Superagent: A customer service chatbot for e-commerce websites. In Proceedings of ACL 2017, System Demonstrations (pp. 97-102).
• DAMIANO, L., & DUMOUCHEL, P. (2018). Anthropomorphism in human–robot co-evolution. Frontiers in psychology, 9, 468.
• DEVELLIS, R. F. (2017). Scale development: Theory and applications. Los Angeles: SAGE.
• DUIJST, D. (2017). Can we improve the user experience of chatbots with personalisation. Master's thesis. University of Amsterdam.
• ELSHOLZ, E., CHAMBERLAIN, J., & KRUSCHWITZ, U. (2019). Exploring Language Style in Chatbots to Increase Perceived Product Value and User Engagement. In L. Azzopardi, M. Halvey, I. Ruthven, H. Joho, V. Murdock, & P. Qvarfordt (Eds.), Proceedings of the 2019 Conference on Human Information Interaction and Retrieval (pp. 301–305). New York, NY, USA: ACM. https://doi.org/10.1145/3295750.3298956
• FINSTAD, K., (2010). Response interpolation and scale sensitivity: Evidence against 5-point scales. Journal of Usability Studies,5(3), pp.104-110
• FITZPATRICK, G. (2018). A short history of human computer interaction: A people-centred perspective. In Proceedings of the 2018 ACM SIGUCCS Annual Conference (pp. 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, October). What makes users trust a chatbot for customer service? An exploratory interview study. In International Conference on Internet Science (pp. 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 (Vol. 2101, pp. 62-70).
• GENTSCH, P. (2018). Conversational AI: How (Chat)Bots Will Reshape the Digital Experience. AI in Marketing, Sales and Service, 81-125. doi:10.1007/978-3-319-89957-2_4
• GNEWUCH, U., MORANA, S., & MAEDCHE, A. (2017, December). Towards Designing Cooperative and Social Conversational Agents for Customer Service. In ICIS.
• HINSON, R., BOATENG, H., RENNER, A., & KOSIBA, J. P. B. (2019). Antecedents and consequences of customer engagement on Facebook. Journal of Research in Interactive Marketing.
• HOLLEBEEK, L., (2011). Exploring customer brand engagement: definition and themes. Journal of strategic Marketing, 19(7), pp.555-573.
• HONG, J. W., CHOI, S., & WILLIAMS, D. (2020). Sexist AI: An Experiment Integrating CASA and ELM. International Journal of Human–Computer Interaction, 1-14.
• 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
• 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. and PILELIENĖ, L., (2018). Can machines paint?. 5th International Multidisciplinary Scientific Conference on Social Sciences and Arts SGEM 2018, 18(6.3), pp. 109–116.
• ISRAFILZADE, K. (2020). What's in a name? Experiment on the aesthetic judgments of art produced by artificial intelligence. Journal of Arts, 3(2), pp. 143-158.
• ISRAFILZADE, K., & BABAYEV, N. (2020). Millennial Versus Non-Millennial Users: Context Of Customer Engagement Levels On Instagram Stories (Extended Version). Journal of Life Economics, 7(2), 135-150.
• KRAFFT, M., Arden, C. M., & Verhoef, P. C. (2017). Permission marketing and privacy concerns—Why do customers (not) grant permissions?. Journal of interactive marketing, 39, 39-54.
• KULIGOWSKA, K. (2015). Commercial chatbot: performance evaluation, usability metrics and quality standards of embodied conversational agents. Professionals Center for Business Research, 2.
• KUMAR, V., AKSOY, L., DONKERS, B., VENKATESAN, R., WIESEL, T., & TILLMANNS, S. (2010). Undervalued or overvalued customers: capturing total customer engagement value. Journal of service research, 13(3), 297-310.
• LEBEUF, C. R. (2018). A taxonomy of software bots: towards a deeper understanding of software bot characteristics
• LECKIE, C., NYADZAYO, M. W., & JOHNSON, L. W. (2016). Antecedents of consumer brand engagement and brand loyalty. Journal of Marketing Management, 32(5-6), 558-578.
• LOCKE, C., LEVINE, R., SEARLS, D. and WEINBERGER, D., (2001). The cluetrain manifesto. Cambridge: Perseus Pub.
• LUO, X., TONG, S., FANG, Z., & QU, Z. (2019). Frontiers: Machines vs. humans: The impact of artificial intelligence chatbot disclosure on customer purchases. Marketing Science, 38(6), 937-947.
• LYNN, M. R. (1986). Determination and quantification of content validity. Nursing research.
• MASLOWSKA, E., MALTHOUSE, E. C., & COLLINGER, T. (2016). The customer engagement ecosystem. Journal of Marketing Management, 32(5-6), 469-501.
• MUIR, K., JOINSON, A., COTTERILL, R., & DEWDNEY, N. (2017). Linguistic style accommodation shapes impression formation and rapport in computer-mediated communication. Journal of Language and Social Psychology, 36(5), 525-548.
• NETEMEYER, R.G., Bearden, W.O. and Sharma, S., (2003). Scaling procedures: Issues and applications. Sage Publications.
• NORMAN, K. L. (2017). Cyberpsychology: An introduction to human-computer interaction. Cambridge university press.
• PFEUFFER, N., BENLIAN, A., GIMPEL, H., & HINZ, O. (2019b). Anthropomorphic information systems. Business & Information Systems Engineering, 61(4), 523-533.
• RAMESH, K., RAVISHANKARAN, S., JOSHI, A., & CHANDRASEKARAN, K. (2017, May). A survey of design techniques for conversational agents. In International Conference on Information, Communication and Computing Technology (pp. 336-350). Springer, Singapore.
• SAYGIN, A. P., CHAMINADE, T., ISHIGURO, H., DRIVER, J., & FRITH, C. (2011). The thing that should not be: Predictive coding and the uncanny valley in perceiving human and humanoid robot actions. Social Cognitive and Affective Neuroscience, 7(4), 413-422. doi:10.1093/scan/nsr025
• SCHUETZLER, R. M., GRIMES, G. M., GIBONEY, J. S., & BUCKMAN, J. (2014). Facilitating Natural Conversational Agent Interactions: Lessons from a Deception Experiment. Proceedings of the International Conference on Information Systems (ICIS), 1–16
• SHUM, H. Y., HE, X. D., & LI, D. (2018). From Eliza to XiaoIce: challenges and opportunities with social chatbots. Frontiers of Information Technology & Electronic Engineering, 19(1), 10-26.
• SO, K. K. F., KING, C., SPARKS, B. A., & WANG, Y. (2016). Enhancing customer relationships with retail service brands: The role of customer engagement. Journal of Service Management, 27(2), 170-193.
• SOTOLONGO, N., & COPULSKY, J. (2018). Conversational marketing: Creating compelling customer connections. Applied Marketing Analytics, 4(1), 6-21.
• THOMAS, E. (2020). EBay Partners With Google Assistant To Bring Voice Control To EBay's Android App. eBay Partners with Google Assistant to Bring Voice Control to eBay's Android App. https://tech.ebayinc.com/product/ebay-partners-with-google-assistant-to-bring-voice-control-to-ebays-android-app/.
• THOMAZ, F., SALGE, C., KARAHANNA, E., & HULLAND, J. (2020). Learning from the Dark Web: leveraging conversational agents in the era of hyper-privacy to enhance marketing. Journal of the Academy of Marketing Science, 48(1), 43–63. https://doi.org/10.1007/s11747-019-00704-3
• TOURÉ-TILLERY, M., & MCGILL, A. L. (2015). Who or what to believe: Trust and the differential persuasiveness of human and anthropomorphised messengers. Journal of Marketing, 79(4), 94-110.
• VAN PINXTEREN, M. M., WETZELS, R. W., RÜGER, J., PLUYMAEKERS, M., & WETZELS, M. (2019). Trust in humanoid robots: implications for services marketing. Journal of Services Marketing.
• 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
• XU, A., LIU, Z., GUO, Y., SINHA, V., & AKKIRAJU, R. (2017). A new chatbot for customer service on social media. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (pp. 3506-3510).
• YIN, Z., CHANG, K. H., & ZHANG, R. (2017). Deepprobe: Information directed sequence understanding and chatbot design via recurrent neural networks. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 2131-2139).
• YUSOFF, M. S. B. (2019). ABC of content validation and content validity index calculation. RESOURCE, 11(2).
• ZADROZNY, W., BUDZIKOWSKA, M., CHAI, J., KAMBHATLA, N., LEVESQUE, S., & NICOLOV, N. (2000). Natural language dialogue for personalised interaction. Communications of the ACM, 43(8), 116-120.