Conversational marketing as a framework for interaction with the customer: Development & validation of the conversational agent's usage scale
Open accessAbstract
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.
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Cites
Yaşlı Kadınlarda Üreme Sağlığı
Kokanalı, D., & Engin Üstün, Y. (n.d.) · DergiPark (Istanbul University) · Cited by 170,090 · see citing works
A Paradigm for Developing Better Measures of Marketing Constructs
Churchill, G. A. (1979) · Journal of Marketing Research · doi:10.1177/002224377901600110 · Cited by 16,549 · see citing works
(1991) · Cited by 15,554 · see citing works
Determination and Quantification Of Content Validity
LYNN, M. R. (1986) · Nursing Research · doi:10.1097/00006199-198611000-00017 · Cited by 6,775 · see citing works
ABC of content validation and content validity index calculation
Department of Medical Education, S. O. M. S., & Yusoff, M. S. B. (2019) · Education in Medicine Journal · doi:10.21315/eimj2019.11.2.6 · Cited by 2,098 · see citing works
(2003) · Cited by 2,093 · see citing works
Exploring customer brand engagement: definition and themes
Hollebeek, L. D. (2011) · Journal of Strategic Marketing · doi:10.1080/0965254x.2011.599493 · Cited by 1,389 · see citing works
Undervalued or overvalued customers: Capturing total customer engagement value
Kumar, V., Aksoy, L., Donkers, B., Venkatesan, R., Wiesel, T., & Tillmanns, S. (2010) · Journal of Service Research · doi:10.1177/1094670510375602 · Cited by 1,382 · see citing works
AI-based chatbots in customer service and their effects on user compliance
Adam, M., Wessel, M., & Benlian, A. (2021) · Electronic Markets · doi:10.1007/s12525-020-00414-7 · Cited by 1,195 · see citing works
Ashfaq, M., Yun, J., Yu, S., & Loureiro, S. M. C. (2020) · Telematics and Informatics · doi:10.1016/j.tele.2020.101473 · Cited by 1,100 · see citing works
Luo, X., Tong, S., Fang, Z., & Qu, Z. (2019) · Marketing Science · doi:10.1287/mksc.2019.1192 · Cited by 1,027 · see citing works
Chatbot e-service and customer satisfaction regarding luxury brands
Chung, M., Ko, E., Joung, H., & Kim, S. J. (2018) · Journal of Business Research · doi:10.1016/j.jbusres.2018.10.004 · Cited by 1,005 · see citing works
Introduction to Structural Equation Modelling Using SPSS and AMOS
Blunch, N. J. (2008) · SAGE Publications Ltd eBooks · doi:10.4135/9781446249345 · Cited by 758 · see citing works
From Eliza to XiaoIce: Challenges and opportunities with social chatbots
Shum, H.-Y., He, X.-D., & Li, D. (2018) · Frontiers of Information Technology & Electronic Engineering · doi:10.1631/fitee.1700826 · Cited by 749 · see citing works
In the shades of the uncanny valley: An experimental study of human–chatbot interaction
Ciechanowski, L., Przegalińska, A., Magnuski, M., & Gloor, P. A. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2018.01.055 · Cited by 680 · see citing works
Response interpolation and scale sensitivity: evidence against 5-point scales
Finstad, K. (2010) · Journal of Usability Studies archive · Cited by 591 · see citing works
A New Chatbot for Customer Service on Social Media
Xu, A., Liu, Z., Guo, Y., Sinha, V. S., & Akkiraju, R. (2017) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3025453.3025496 · Cited by 589 · see citing works
Trust in humanoid robots: implications for services marketing
van Pinxteren, M. M. E., Wetzels, R. W. H., Rüger, J., Pluymaekers, M., & Wetzels, M. G. M. (2019) · Journal of Services Marketing · doi:10.1108/jsm-01-2018-0045 · Cited by 544 · see citing works
Chatbots and the new world of HCI
Følstad, A., & Brandtzæg, P. B. (2017) · interactions · doi:10.1145/3085558 · Cited by 520 · see citing works
Saygin, A. P., Chaminade, T., Ishiguro, H., Driver, J., & Frith, C. (2012) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsr025 · Cited by 452 · see citing works
What Makes Users Trust a Chatbot for Customer Service? An Exploratory Interview Study
Følstad, A., Nordheim, C. B., & Bjørkli, C. A. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01437-7_16 · Cited by 360 · see citing works
SuperAgent: A Customer Service Chatbot for E-commerce Websites
Cui, L., Huang, S., Wei, F., Tan, C., Duan, C., & Zhou, M. (2017) · Annual Meeting of the Association for Computational Linguistics: System Demonstrations (ACL Demo) · doi:10.18653/v1/p17-4017 · Cited by 357 · see citing works
A Survey on Conversational Agents/Chatbots Classification and Design Techniques
Hussain, S., Ameri Sianaki, O., & Ababneh, N. (2019) · Advances in Intelligent Systems and Computing · doi:10.1007/978-3-030-15035-8_93 · Cited by 279 · see citing works
Anthropomorphism in Human–Robot Co-evolution
Damiano, L., & Dumouchel, P. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.00468 · Cited by 256 · see citing works
The customer engagement ecosystem
Masłowska, E., Malthouse, E. C., & Collinger, T. (2016) · Journal of Marketing Management · doi:10.1080/0267257x.2015.1134628 · Cited by 220 · see citing works
Towards Designing Cooperative and Social Conversational Agents for Customer Service
Gnewuch, U., Morana, S., & Mädche, A. (2017) · Journal of the Association for Information Systems · Cited by 211 · see citing works
Thomaz, F., Salge, C., Karahanna, E., & Hulland, J. (2020) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-019-00704-3 · Cited by 204 · see citing works
Artificial Intelligence for Business
Akerkar, R. A. (2018) · SpringerBriefs in business · doi:10.1007/978-3-319-97436-1 · Cited by 191 · see citing works
Permission Marketing and Privacy Concerns — Why Do Customers (Not) Grant Permissions?
Krafft, M., Arden, C. M., & Verhoef, P. C. (2017) · Journal of Interactive Marketing · doi:10.1016/j.intmar.2017.03.001 · Cited by 171 · see citing works
A Survey of Design Techniques for Conversational Agents
Ramesh, K., Ravishankaran, S., Joshi, A., & Chandrasekaran, K. (2017) · Communications in computer and information science · doi:10.1007/978-981-10-6544-6_31 · Cited by 170 · see citing works
Antecedents and consequences of customer engagement on Facebook
Hinson, R. E., Boateng, H., Renner, A., & Kosiba, J. P. (2019) · Journal of Research in Interactive Marketing · doi:10.1108/jrim-04-2018-0059 · Cited by 160 · see citing works
Anthropomorphic Information Systems
Pfeuffer, N., Benlian, A., Gimpel, H., & Hinz, O. F. (2019) · Business & Information Systems Engineering · doi:10.1007/s12599-019-00599-y · Cited by 150 · see citing works
The Customer Engagement EcosystemPreprint
Masłowska, E., Malthouse, E. C., & Collinger, T. (2015) · SSRN Electronic Journal · doi:10.2139/ssrn.2694040 · Cited by 143 · see citing works
Conversational agents in business: A systematic literature review and future research directions
Bavaresco, R., Silveira, D., Reis, E., Barbosa, J., Righi, R., Costa, C., Antunes, R., Gomes, M., Gatti, C., Vanzin, M., et al. (2020) · Computer Science Review · doi:10.1016/j.cosrev.2020.100239 · Cited by 143 · see citing works
Kuligowska, K. (2015) · Professionals Center for Business Research · doi:10.18483/pcbr.22 · Cited by 97 · see citing works
Survey on Intelligent Chatbots: State-of-the-Art and Future Research Directions
Almansor, E. H., & Hussain, F. K. (2019) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-22354-0_47 · Cited by 96 · see citing works
Cyberpsychology: an introduction to human-computer interaction
(2009) · Choice Reviews Online · doi:10.5860/choice.46-2716 · Cited by 71 · see citing works
Exploring Language Style in Chatbots to Increase Perceived Product Value and User Engagement
Elsholz, E., Chamberlain, J., & Kruschwitz, U. (2019) · Conference on Human Information Interaction and Retrieval · doi:10.1145/3295750.3298956 · Cited by 60 · see citing works
Muir, K., Joinson, A., Cotterill, R., & Dewdney, N. (2017) · Journal of Language and Social Psychology · doi:10.1177/0261927x17701327 · Cited by 55 · see citing works
Yin, Z., Chang, K.-H., & Zhang, R. (2017) · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3097983.3098148 · Cited by 45 · see citing works
Overview of the sixth dialog system technology challenge: DSTC6
Hori, C., Pérez, J., Higashinaka, R., Hori, T., Boureau, Y.-L., Inaba, M., Tsunomori, Y., Takahashi, T., Yoshino, K., & Kim, S. (2018) · Computer Speech & Language · doi:10.1016/j.csl.2018.09.004 · Cited by 43 · see citing works
Facilitating Natural Conversational Agent Interactions: Lessons from a Deception Experiment
Schuetzler, R. M., Grimes, G. M., Giboney, J. S., & Buckman, J. R. (2014) · DigitalCommons@UNO · Cited by 38 · see citing works
Sexist AI: An Experiment Integrating CASA and ELM
Hong, J.-W., Choi, S., & Williams, D. C. (2020) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2020.1801226 · Cited by 36 · see citing works
Chatbots and conversational interfaces: Three domains of use
Valtolina, S., Barricelli, B. R., Gaetano, S. D., & Diliberto, P. (2018) · Institutional Research Information System (Università degli Studi di Brescia) · Cited by 35 · see citing works
Conversational marketing: Creating compelling customer connections
Sotolongo, N., & Copulsky, J. R. (2018) · Applied marketing analytics · doi:10.69554/ircx9392 · Cited by 30 · see citing works
Recent Advances on Human-Computer Dialogue
Wang, X., & Yuan, C. (2016) · CAAI Transactions on Intelligence Technology · doi:10.1016/j.trit.2016.12.004 · Cited by 29 · see citing works
Conversational AI: How (Chat)Bots Will Reshape the Digital Experience
Gentsch, P. (2018) · Springer eBooks · doi:10.1007/978-3-319-89957-2_4 · Cited by 29 · see citing works
On the construction of more human-like chatbots: Affect and emotion analysis of movie dialogue data
Banchs, R. E. (2017) · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · doi:10.1109/apsipa.2017.8282245 · Cited by 25 · see citing works
An Efficient Search for Context-Based Chatbots
Atiyah, A., Jusoh, S., & Almajali, S. (2018) · doi:10.1109/csit.2018.8486187 · Cited by 20 · see citing works
WHAT S IN A NAME EXPERIMENT ON THE AESTHETIC JUDGMENTS OF ART PRODUCED BY ARTIFICIAL INTELLIGENCE
Israfilzade, K. (2020) · JOURNAL OF ARTS · doi:10.31566/arts.3.011 · Cited by 20 · see citing works
Self-citationA taxonomy of software bots: towards a deeper understanding of software bot characteristics
Lebeuf, C. (2018) · UVic’s Research and Learning Repository (University of Victoria) · Cited by 19 · see citing works
Can we Improve the User Experience of Chatbots with Personalisation?
Duijst, D. (2017) · doi:10.13140/rg.2.2.36112.92165 · Cited by 18 · see citing works
Israfilzade, K., & Babayev, N. (2020) · Journal of Life Economics · doi:10.15637/jlecon.7.009 · Cited by 8 · see citing works
Self-citationCancel, D., Gerhardt, D., & Devaney, E. (2019) · Cited by 7 · see citing works
Israfilzade, K. (2018) · SGEM International Multidisciplinary Scientific Conferences on Social Sciences and Arts · doi:10.5593/sgemsocialf2018/6.3/s12.014 · Cited by 2 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 9
- AGUIRRE, E., ROGGEVEEN, A. L., Grewal, D., & Wetzels, M. (2016). The personalisation-privacy paradox: implications for new media. Journal of Consumer Marketing.
- 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 Re- search, 56(1), 39-52.
- CAMBRIDGE ENGLISH DICTIONARY (2020). Conversation. CONVERSATION | meaning in the Cambridge English Dictio- nary. https://dictionary.cambridge.org/dictionary/english/conversa- tion?q=Conversation.
- FITZPATRICK, G. (2018). A short history of human computer in- teraction: A people-centred perspective. In Proceedings of the 2018 ACM SIGUCCS Annual Conference (pp. 3-3).
- LOCKE, C., LEVINE, R., SEARLS, D. and WEINBERGER, D., (2001). The cluetrain manifesto. Cambridge: Perseus Pub.
- SO, K. K. F., KING, C., SPARKS, B. A., & WANG, Y. (2016). En- hancing customer relationships with retail service brands: The role of customer engagement. Journal of Service Management, 27(2), 170-193.
- TOURÉ-TILLERY, M., & MCGILL, A. L. (2015). Who or what to believe: Trust and the differential persuasiveness of human and an- thropomorphised messengers. Journal of Marketing, 79(4), 94-110.
- YIN, Z., CHANG, K. H., & ZHANG, R. (2017). Deepprobe: Infor- mation directed sequence understanding and chatbot design via re- current neural networks. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Min- ing (pp. 2131-2139).
- ZADROZNY, W., BUDZIKOWSKA, M., CHAI, J., KAMBHAT- LA, N., LEVESQUE, S., & NICOLOV, N. (2000). Natural lan- guage dialogue for personalised interaction. Communications of the ACM, 43(8), 116-120.
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- Authors
- Israfilzade, K.
- Affiliations
- Vytautas Magnus University (LT)
- Corresponding author
- Israfilzade, Khalil
- ORCID
- Israfilzade, Khalil
- Venue
- JOURNAL OF LIFE ECONOMICS
- Publisher
- Holistence Publications
- Published
- 2021-10-31
- Volume
- 8
- Issue
- 4
- Pages
- 533-546
- ISSN
- 2148-4139 (ISSN-L)
- OpenAlex
- W3213429103
- Cited by
- 23
- References
- 55
- Citations by year
- 2026: 3 · 2025: 6 · 2024: 9 · 2023: 3 · 2022: 2
- FWCI
- 1.24
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Journal of Life Economics (publishedVersion, cc-by)
- DergiPark (Istanbul University) (submittedVersion)
- Vytautas Magnus University (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Customer Service Quality and Loyalty
- Keywords
- conversational marketing, chatbots, scale development, scale validation, customer interaction, customer service, e-commerce, personalized dialogue
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