Academia.eduAcademia.edu

Outline

Title
Abstract
Key Takeaways
Figures
Introduction
Background
Literature Review
Chatbot Design and Techniques in Marketing
References

A Survey on the Impact of Chatbots on Marketing Activities

Profile image of Dhamyaa NasrawiDhamyaa Nasrawi
https://doi.org/10.1109/ICCCNT54827.2022.9984635
visibility

…

description

7 pages

link

1 file

Abstract

Recently, chatbot technology has been employed in several customer services and support roles. These conversational agents have become valuable assets to companies and organizations because of their ability to communicate with humans and process large amounts of data. Furthermore, since most customers are using online shopping to fulfill their requirements instead of traditional methods, they expect to get a full 24-hour service. This survey provides an overview of different studies that used chatbots as a tool to provide customer service and analyzes the techniques applied to it. In this survey, we divided the studies into two parts, the algorithms, techniques used in creating a chatbot, and the influence of the chatbot's use on marketing. Research shows most of the studies used Deep learning techniques for building chatbots. In addition, chatbot provides services that enable customers to have better communication with the brand and affect their long-term relationships.

Key takeaways
sparkles

AI

  1. Chatbots significantly enhance customer engagement and satisfaction in marketing activities.
  2. Deep learning techniques dominate the development of effective chatbots for customer service.
  3. The survey categorizes chatbots into retrieval-based and generative-based models, each with distinct functionalities.
  4. Chatbots provide 24/7 support, which is crucial for modern digital marketing strategies.
  5. Research indicates that chatbots positively influence long-term customer-brand relationships.
Figures (3)
3. Benefits of Chatbots on Customer Service The generative-based model can build new responses from scratch without relying on predefined responses. Generative model based on machine-translation techniques. This model's probability of making grammatical mistakes is high [34],[35]. Conversational chatbots are a new type of customer service; their main benefit is fast and accessible help. All studies reported that the rapid response of chatbots was accentuated [36]. In today’s world, many businesses rely on bots to do their work. In addition, bots help save money and provide other benefits for the business [37]. Here are some benefits of chatbots in marketing technology:
3. Benefits of Chatbots on Customer Service The generative-based model can build new responses from scratch without relying on predefined responses. Generative model based on machine-translation techniques. This model's probability of making grammatical mistakes is high [34],[35]. Conversational chatbots are a new type of customer service; their main benefit is fast and accessible help. All studies reported that the rapid response of chatbots was accentuated [36]. In today’s world, many businesses rely on bots to do their work. In addition, bots help save money and provide other benefits for the business [37]. Here are some benefits of chatbots in marketing technology:
interactive dialogue. However, the study was limited by the generalizability of its data (157 Korean students) and a few luxury brands. Participants did not try to use the Chatbot; they just looked at the interface of it for the Burberry brand and answered the questionnaire. If they had tested a real Chatbot experiment, it would have given more effective results. Various brands use chatbots for multiple purposes, such as marketing or improving customer service. B. Influence of Chatbot on Marketing Chung et al., 2020 [49] studied the effect of chatbots on customer satisfaction in the context of luxury brands. They tested the five dimensions of Chatbot, including interacting with customers, entertainment, trend, personalization, and problem-solving. The study found that users who interacted with Chatbots were more satisfied than those who didn’t. This study also revealed that the digital context can enhance company—customer connections and shopping experiences. Researchers find that chatbots lead to higher customer satisfaction because they engage the customer and provide
interactive dialogue. However, the study was limited by the generalizability of its data (157 Korean students) and a few luxury brands. Participants did not try to use the Chatbot; they just looked at the interface of it for the Burberry brand and answered the questionnaire. If they had tested a real Chatbot experiment, it would have given more effective results. Various brands use chatbots for multiple purposes, such as marketing or improving customer service. B. Influence of Chatbot on Marketing Chung et al., 2020 [49] studied the effect of chatbots on customer satisfaction in the context of luxury brands. They tested the five dimensions of Chatbot, including interacting with customers, entertainment, trend, personalization, and problem-solving. The study found that users who interacted with Chatbots were more satisfied than those who didn’t. This study also revealed that the digital context can enhance company—customer connections and shopping experiences. Researchers find that chatbots lead to higher customer satisfaction because they engage the customer and provide
experiment. One hundred four participants took part in the study on hedonic goods, while 80 took part in the study on utilitarian goods. The study was conducted in an academic computer laboratory for two months. Participants answered questions about their knowledge of specific brands and their previous experience with the Chatbot. Two conditions were defined in the experiment, and the participants were divided according to the two conditions into two groups: a control group that only used the website and the second group was an experimental group that used the Chatbot. The results show that the perception of utility after using Chatbot was different compared without it and significantly impacted the product value perception and purchase intention. In addition, chatbots increase the hedonics of utilitarian products. Lo Presti et al., 2021 [51] Propose this study to focus on chatbots during online purchasing and their impact on customer purchases. The study has been conducted on university students (N=184), as they are the age group that uses Internet services. The researchers wanted to investigate the Chatbot's role in product hedonic/utilitarian value. Two products (cruise travel, telephone service) were chosen for the user with high accuracy. However, from the survey above, it can be said that the implementation of Chatbot in marketing has high leverage in improving marketing activities and gaining high customer satisfaction. In addition, chatbots affect the relationship between customers and brands in the long term.
experiment. One hundred four participants took part in the study on hedonic goods, while 80 took part in the study on utilitarian goods. The study was conducted in an academic computer laboratory for two months. Participants answered questions about their knowledge of specific brands and their previous experience with the Chatbot. Two conditions were defined in the experiment, and the participants were divided according to the two conditions into two groups: a control group that only used the website and the second group was an experimental group that used the Chatbot. The results show that the perception of utility after using Chatbot was different compared without it and significantly impacted the product value perception and purchase intention. In addition, chatbots increase the hedonics of utilitarian products. Lo Presti et al., 2021 [51] Propose this study to focus on chatbots during online purchasing and their impact on customer purchases. The study has been conducted on university students (N=184), as they are the age group that uses Internet services. The researchers wanted to investigate the Chatbot's role in product hedonic/utilitarian value. Two products (cruise travel, telephone service) were chosen for the user with high accuracy. However, from the survey above, it can be said that the implementation of Chatbot in marketing has high leverage in improving marketing activities and gaining high customer satisfaction. In addition, chatbots affect the relationship between customers and brands in the long term.

Related papers

EXPLORING THE IMPACT OF AI CHATBOTS ON CUSTOMER SATISFACTION
Vivian Vu, IJCIRAS Research Publication

IJCIRAS, 2022

Artificial intelligence (AI) has revolutionized the ecommerce experience and opened up new ways for businesses to communicate with customers through chatbots. This study aims to investigate how factors of chatbots influence customer satisfaction in ecommerce. A quantitative approach was adopted to explore the impact of usability, responsiveness, perceived trust, accessibility, and empathy on customer satisfaction. Empirical data was collected from 317 participants through an online survey and was analyzed using regression analysis by SPSS. The results indicate that usability, perceived trust, and empathy have significant positive effects on customer satisfaction, which paves way for future studies to enrich the research field. The study also presents practical insights to managers, chatbot designers, and customer service units in improving chatbots and enhancing customer satisfaction.

View PDFchevron_right
A Comparative Analysis of Customer Service Chatbots: Efficiency, Usability and Application
Md Humaion Kabir Mehedi, Lamia Kefaiat

2023 Computer Applications & Technological Solutions (CATS), 2024

A computer programme that imitates and processes human interaction, either through the use of voice or text communication, is known as a chatbot. Its purpose is to be of assistance in the process of finding a solution to a problem. The transformation brought on by advances in technology has had an effect on every industry. The chatbot provides assistance with a wide variety of tasks, including Reservations, Customer Service, and a great number of other services. The fast development of technologies relating to artificial intelligence and natural language processing has resulted in an increase in the use of chatbots in a variety of fields, most notably in the field of customer service. Customers could receive advice that is prompt, accurate, and personalised through the use of chatbots, which has the potential to completely transform customer service. Because it can automate customer service and reduce the amount of work that needs to be done by humans, it has gained a lot of popularity in the business world. Which can help businesses improve the experience they provide for their customers. The purpose of this research is to undertake a comparative review of customer service chatbots, with a particular emphasis on their efficiency, usability, and application across a variety of business sectors. The research will uncover best practises, difficulties, and potential for improvement by analysing a variety of chatbot solutions.

View PDFchevron_right
Customer Service Chatbots: A Qualitative Interview Study into the Communication Journey of Customers
Laura Hafkamp

2020

The current qualitative interview study describes the communication journey of customers who wish to contact companies, and their evaluation of chatbot communication within this journey. Interviews were conducted with a sample (N=24) that was varied in terms of gender, age, educational level and household composition. Experiences with nine customer service chatbots were included. The analysis focuses on three stages in the journey: first, customers' prior expectations when contacting a company; second, their experiences during chatbot conversations, and third, their final conclusions about under which conditions customer service chatbots should be implemented, and the consequences of chatbot communication for customers' company perceptions. Implications for research and practice are discussed.

View PDFchevron_right
Language Model-Driven Chatbot for Business to Address Marketing and Selection of Products
AMIT KUSHWAHA

Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation, 2020

Artificial Intelligence has been increasingly gaining acceptance across advanced functions in numerous fields and industries. This includes marketing, customer support, and leads generation in healthcare, transportation, education, and off late in e-commerce. Machine learning as a subset of artificial intelligence techniques provides various algorithms that enable machines to learn from historical data and make realtime predictions on numbers and texts. Most of the businesses nowadays are trying to increase their reach and making sure that they are available to cater to the customers when they need help. This also enables the companies to market and respond to the queries of potential customers on a realtime basis. Chatter robots or chatbot is one such application of machine learning which allows the business to provide round the clock support to customers and potential leads for marketing questions. Most of the business fail to venture in the domain of hosting chatbot on the website as they do not have enough conversational data with them to train the machine learning algorithm and wait for years to collect enough sample. With the proposed language model-driven chatbots, businesses starting fresh in the domain of the hosting this application can use the user-generated content on social media to fuel the backend framework for the chatbots and start hosting the application.

View PDFchevron_right
Customer-brand relationship in the era of artificial intelligence: understanding the role of chatbot marketing efforts
Yang Cheng

journal of product and brand management , 2021

Purpose-This study aims to explore the role of artificial intelligence (AI)-powered chatbot marketing efforts (CMEs) in the establishment of relationships between brands and their customers, extending the link between relationship marketing and online consumer behavioral intentions. Design/methodology/approach-Data are collected from 1,072 customers in the USA, who used chatbot marketing activities from any of 30 brands leading their industries in messaging innovation. Structural equation modeling is used for data analysis. Findings-Results show that interaction, information, accessibility, entertainment and customization are important CMEs components. CMEs have significant direct effects on the quality of communication with chatbot agents and indirectly affect customer-brand relationships (CBR) and customer response. In addition, the findings demonstrate that CBR mediates the association between communication quality and customer response. Originality/value-Implications of this study can enable practitioners to understand the effects of AI on user experiences and provide a guide for the development of CMEs strategies and relationship building.

View PDFchevron_right
Chatbots for Brand Representation in Comparison with Traditional Websites
Martin Ebner

nternational Journal of Interactive Mobile Technologies (iJIM) , 2020

Chatbots have gained enormous popularity in recent years. IT giants such as Microsoft, Google and Facebook have taken an interest in automated conversations. Messaging apps like WhatsApp and Facebook Messenger are playing an increasingly important role in smartphone usage and communication in general perfect conditions for chatbots. This paper provides an introduction of recent chatbot development in general and in customer environments. As part of this work, a chatbot was developed for the Austrian IT company CodeFluegel GmbH. The chatbot, named Theodore, provides information about CodeFluegel via Facebook Messenger and webchat, like the existing company website. The design process and implementation of the chatbot as well as architectural considerations are explained throughout this document. In a user study, participants perform typical tasks with the website and the chatbot. The usage of both platforms is evaluated in order to identify advantages and disadvantages as well as differences compared to the other technology and to draw conclusions. Findings to this study indicate promising prospects for chatbots as alternative touchpoints for customers and others and a way to replace and enhance traditional websites.

View PDFchevron_right
Role of Chatbot in Customer Service: A Study from the Perspectives of the Banking Industry of Bangladesh
Tama Saha

2019

The use of robots in live chats often known as chatbots is an emerging, smart and readily adoptable technology. It is also now a common customer service strategy as this is very much beneficial in rendering various customer services such as one-to-one conversations, customized offer, responsive customer service through 24/7/365 availability, etc. From this perspective the current study is an attempt to examine the role of chatbot in customer service of the banking industry of Bangladesh. The current study is the embodiment of both primary and secondary data collection and their analyses in which, the secondary data have been collected from the recent research findings and the primary data have been collected during the month of September 1, 2019 to November 30, 2019 from the sample size of 125 respondents including users and employees of digital banking service providers using judgment sampling method through a structured and self-administered questionnaire. The current study found the feasibility of using chatbots because of its varied forms of benefits in rendering customer service which include i) gathering feedback and suggestions from the customers via simple questionanswer interaction so that the lead page of the website of the concerned organization can be improved, ii) assisting users in navigation on the site, to limit the amount of clicks and to shorten the time to reach the desired information or product so that social relationships and emotional bond with customers can be built by increasing their confidence in the company, iii) using Natural Language Processing (NLP) to give unique feel in human-like conversations and personalized response to its customers and many more. Thus, chatbots centric services can be considered to enable effective customer service and thus ensure business growth and development of the online banking in Bangladesh.

View PDFchevron_right
Customer Service 2.0: The Influence of Chatbots and AI Solutions
MAHENDAR GOLI

MATEC web of conferences, 2024

In recent years, chatbots have gained popularity as a result of breakthroughs in artificial intelligence and other technologies that lie behind the surface. In a similar vein, the growing interactivity of the internet and the enhanced capabilities of mobile devices have notably drawn a greater number of customers who are looking for improved and personalized customer care. This is the goal. Therefore, the purpose of this chapter was to gain a better understanding of the usage of chatbots by online businesses in order to throw light on the influence that it has on the happiness of customers with customer service. In this particular research endeavor, the conceptual framework was built using the commitment trust theory, which served as the underlying theoretical underpinning. It investigated the connections between trust, commitment, service quality, and technology in regard to the utilization of chatbots. As a consequence, the higher level of customer involvement that was achieved has resulted in increased information sharing and referrals to additional clients. The purpose of this chapter was to propose an integrated framework for anticipating the use of chatbots to increase customer bonding with businesses. The most important contribution was the compilation of a list of prerequisites that must be met in order to enhance customer involvement in the process of implementing chatbots.

View PDFchevron_right
A Review of How to Use Chatbots in the Future
M.tri Saputra

Proceedings of International Conference on Economics Business and Government Challenges

The current, rapid advancement of technology across all fields, including services based on artificial intelligence (AI), serves as the driving force for this study. In contrast to other forms of AI technology, chatbots may interact with clients directly and without human intervention. According to the studied research, chatbots have a chance of failing. Additionally, if the "practice" data utilized is not as exact, the dialogue cannot be understood, and last but not least, secure personal data. Chatbots are not a new concept, but they still have room for development. Additionally, it is envisaged that industry participants will gain knowledge of the function of automation so they may use chatbots to boost business profitability and provide efficiency in many operational fields. Keywords: Perceived ease of use; trusts; continuous intention to use; chatbots; literature review

View PDFchevron_right
Understanding the User Experience of Customer Service Chatbots: What Can We Learn from Customer Satisfaction Surveys?
Knut Kvale

Chatbot Research and Design

Understanding and improving user experience is key to strengthening uptake and realizing the potential of chatbots for customer service. In this paper, we investigate customer satisfaction surveys as a source of insight into such user experience. A total of 5,687 customer satisfaction reports on users' interactions with a customer service chatbot, and the corresponding chatbot interactions, are analyzed. The findings demonstrate that customer satisfaction reports are closely associated with the degree to which the problems motivating users' chatbot interactions are resolved. Furthermore, the findings show substantial variation in the performance of different chatbot intents in terms of customer satisfaction and problem resolution. This implies that user experience varies substantially depending on the problems motivating users to interact with the chatbot. Finally, we identify key characteristics of the intents associated with particularly high or low customer experience, suggesting paths towards efficient improvement of chatbot user experience. Based on the findings, we point to key implications for theory and practice and suggest directions for future research.

View PDFchevron_right

References (54)

  1. E. Adamopoulou and L. Moussiades, An Overview of Chatbot Technology, vol. 584 IFIP, no. May. Springer International Publishing, 2020.
  2. K. Kaličanin, M. Čolović, A. Njeguš, and V. Mitić, "Benefits of Artificial Intelligence and Machine Learning in Marketing," May 2019, pp. 472-477, DOI: 10.15308/sinteza-2019-472-477.
  3. B. Abu Shawar and E. Atwell, "Chatbots: are they really useful?," LDV-Forum Zeitschrift für Comput. und Sprachtechnologie, vol. 22, no. 1, pp. 29-49, 2007.
  4. A. Q. Review, "MIND," pp. 433-460, 1950.
  5. J. Weizenbaum, "ELIZA-A Computer Program For the Study of Natural Language Communication Between Man And Machine," Commun. ACM, vol. 26, no. 1, pp. 23-28, 1983, DOI: IEEE -54827 13th ICCCNT 2022 Oct 3-5, 2022 Virtual Conference Authorized licensed use limited to: UNIVERSITY PUTRA MALAYSIA. Downloaded on April 07,2023 at 13:25:27 UTC from IEEE Xplore. Restrictions apply. 10.1145/357980.357991.
  6. S. Fernandes, R. Gawas, P. Alvares, M. Fernandes, D. Kale, and S. Aswell, "Survey on Various Conversational Systems," Int. Conf. Emerg. Trends Inf. Technol. Eng. ic-ETITE 2020, pp. 1-8, 2020, doi: 10.1109/ic-ETITE47903.2020.126.
  7. M. Nuruzzaman and O. K. Hussain, "A Survey on Chatbot Implementation in Customer Service Industry through Deep Neural Networks," in Proceedings -2018 IEEE 15th International Conference on e-Business Engineering, ICEBE 2018, Dec. 2018, pp. 54-61, DOI: 10.1109/ICEBE.2018.00019.
  8. D. Carlander-Reuterfelt, A. Carrera, C. A. Iglesias, O. Araque, J. F. S. Sanchez Rada, and S. Munoz, "JAICOB: A Data Science Chatbot," IEEE Access, vol. 8, pp. 180672-180680, 2020, doi: 10.1109/ACCESS.2020.3024795.
  9. A. N. Mathew, V. Rohini, and J. Paulose, "NLP-based personal learning assistant for school education," Int. J. Electr. Comput. Eng., vol. 11, no. 5, pp. 4522-4530, 2021, DOI: 10.11591/ijece.v11i5.pp4522-4530.
  10. N. Belhaj, A. Hamdan, N. El Houda Chaoui, H. Chaoui, and M. El Bekkali, "Engaging students to fill surveys using chatbots: University case study," Indones. J. Electr. Eng. Comput. Sci., vol. 24, no. 1, pp. 473-483, 2021, DOI: 10.11591/ijeecs.v24.i1.pp473- 483.
  11. E. Amer, A. Hazem, O. Farouk, A. Louca, Y. Mohamed, and M. Ashraf, "A Proposed Chatbot Framework for COVID-19," 2021 Int. Mobile, Intelligent, Ubiquitous Comput. Conf. MIUCC 2021, pp. 263-268, 2021, DOI: 10.1109/MIUCC52538.2021.9447652.
  12. I. Salhi, K. El Guemmat, M. Qbadou, and K. Mansouri, "Towards developing a pocket therapist: An intelligent adaptive psychological support chatbot against mental health disorders in a pandemic situation," Indones. J. Electr. Eng. Comput. Sci., vol. 23, no. 2, pp. 1200-1211, 2021, DOI: 10.11591/ijeecs.v23.i2.pp1200-1211.
  13. U. Kiruthika, S. K. S. Raja, V. Balaji, and C. J. Raman, "E- Agriculture for Direct Marketing of Food Crops Using Chatbots," ICPECTS 2020 -IEEE 2nd Int. Conf. Power, Energy, Control Transm. Syst. Proc., pp. 20-23, 2020, DOI: 10.1109/ICPECTS49113.2020.9337024.
  14. J. T. S. Quah and Y. W. Chua, "Chatbot assisted marketing in financial service industry," in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, vol. 11515 LNCS, pp. 107- 114, DOI: 10.1007/978-3-030-23554-3_8.
  15. M. D. Illescas-Manzano, N. V. López, N. A. González, and C. C. Rodríguez, "Implementation of chatbot in online commerce, and open innovation," J. Open Innov. Technol. Mark. Complex., vol. 7, no. 2, 2021, doi: 10.3390/joitmc7020125.
  16. Z. Yan et al., "DocChat: An information retrieval approach for chatbot engines using unstructured documents," 54th Annu. Meet. Assoc. Comput. Linguist. ACL 2016 -Long Pap., vol. 1, pp. 516- 525, 2016, DOI: 10.18653/v1/p16-1049.
  17. S. Garcia-Mendez, F. De Arriba-Perez, F. J. Gonzalez-Castano, J. A. Regueiro-Janeiro, and F. Gil-Castineira, "Entertainment Chatbot for the Digital Inclusion of Elderly People without Abstraction Capabilities," IEEE Access, vol. 9, pp. 75878-75891, 2021, DOI: 10.1109/ACCESS.2021.3080837.
  18. R. Asadi, Amir-Reza and Hemadi, "Design and implementation of a chatbot for e-commerce," Inf. Commun. Technol. …, no. February, pp. 1-10, 2018, [Online]. Available: https://www.researchgate.net/publication/318738996_SuperAgent_ A_Customer_Service_Chatbot_for_E- commerce_Websites/link/5b5999a10f7e9bc79a65df55/download.
  19. D. Gunawan, F. P. Putri, and H. Media, "Bershca: Bringing chatbot into hotel industry in Indonesia," Telkomnika (Telecommunication Comput. Electron. Control., vol. 18, no. 2, pp. 839-845, 2020, doi: 10.12928/TELKOMNIKA.V18I2.14841.
  20. R. Angeline, T. Gaurav, P. Rampuriya, and S. Dey, "Supermarket Automation with Chatbot and Face Recognition Using IoT and AI," Proc. 3rd Int. Conf. Commun. Electron. Syst. ICCES 2018, no. Icces, pp. 1183-1186, 2018, DOI: 10.1109/CESYS.2018.8723978.
  21. F. Clarizia, F. Colace, M. Lombardi, F. Pascale, and D. Santaniello, Chatbot: An education support system for student, vol. 11161 LNCS. Springer International Publishing, 2018.
  22. S. Singh and H. K. Thakur, "Survey of Various AI Chatbots Based on Technology Used," ICRITO 2020 -IEEE 8th Int. Conf. Reliab. Infocom Technol. Optim. (Trends Futur. Dir., pp. 1074-1079, 2020, DOI: 10.1109/ICRITO48877.2020.9197943.
  23. S. Ponde, "DIGITAL MARKETING: CONCEPTS & ASPECTS.," Int. J. Adv. Res., vol. 7, no. 2, pp. 260-266, Feb. 2019, doi: 10.21474/IJAR01/8483.
  24. E. Van den Broeck, B. Zarouali, and K. Poels, "Chatbot advertising effectiveness: When does the message get through?," Comput. Human Behav., vol. 98, pp. 150-157, Sep. 2019, DOI: 10.1016/j.chb.2019.04.009.
  25. E. Adamopoulou and L. Moussiades, "Chatbots: History, technology, and applications," Mach. Learn. with Appl., vol. 2, p. 100006, Dec. 2020, DOI: 10.1016/j.mlwa.2020.100006.
  26. "CONVERSATIONAL MARKETING HOW THE WORLD'S FASTEST-GROWING COMPANIES USE CHATBOTS TO GENERATE LEADS 24/7/365 (AND HOW YOU CAN TOO) DAVID CANCEL DAVE GERHARDT EDITED BY ERIK DEVANEY."
  27. M. Ashfaq, J. Yun, S. Yu, and S. M. C. Loureiro, "I, Chatbot: Modeling the determinants of users' satisfaction and continuance intention of AI-powered service agents," Telemat. Informatics, vol. 54, Nov. 2020, DOI: 10.1016/j.tele.2020.101473.
  28. S. Janarthanam, Hands-on chatbots and conversational UI development : build chatbots and voice user interfaces with Chatfuel, Dialogflow, Microsoft Bot Framework, Twilio, and Alexa Skills. .
  29. J. Chai, V. Horvath, N. Nicolov, M. Stys-Budzikowska, N. Kambhatla, and W. Zadrozny, "Natural language sales assistant-A web-based dialog system for online sales," Innov. Appl. Artif. Intell. -Conf. Proc., pp. 19-26, 2001.
  30. S. S. Dumpala, "( for Covid-19 and SARS ) by Saikrishna Sattayya Dumpala Student Id : 10540452 Dissertation submitted in partial fulfillment of the requirements for the degree of M . Sc . in Information Systems with Computing at Dublin Business School Supervisor : Obinna ," 2021.
  31. A. Miklosik, N. Evans, and A. M. A. Qureshi, "The Use of Chatbots in Digital Business Transformation: A Systematic Literature Review," IEEE Access, vol. 9. Institute of Electrical and Electronics Engineers Inc., pp. 106530-106539, 2021, DOI: 10.1109/ACCESS.2021.3100885.
  32. P. Muangkammuen, N. Intiruk, and K. R. Saikaew, "Automated Thai-FAQ chatbot using RNN-LSTM," 2018 22nd Int. Comput. Sci.
  33. Eng. Conf. ICSEC 2018, pp. 1-4, 2018, doi: 10.1109/ICSEC.2018.8712781.
  34. B. Borah, D. Pathak, P. Sarmah, B. Som, and S. Nandi, Survey of Textbased Chatbot in Perspective of Recent Technologies, vol. 1031. Springer Singapore, 2019.
  35. S. Hussain, O. Ameri Sianaki, and N. Ababneh, "A Survey on Conversational Agents/Chatbots Classification and Design Techniques," in Advances in Intelligent Systems and Computing, 2019, vol. 927, pp. 946-956, DOI: 10.1007/978-3-030-15035-8_93.
  36. V. A. Bhagwat, "Deep Learning for ChatBots," Scholarworks.Sjsu.Edu, p. 56, 2018, [Online]. Available: https://scholarworks.sjsu.edu/cgi/viewcontent.cgi?article=1645&con text=etd_projects.
  37. A. Følstad, C. B. Nordheim, and C. A. Bjørkli, "What makes users trust a chatbot for customer service? An exploratory interview study," Lect. Notes Comput. Sci. (including Subsea. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 11193 LNCS, pp. 194-208, 2018, DOI: 10.1007/978-3-030-01437-7_16.
  38. S. Raj, Building Chatbots with Python. Apress, 2019.
  39. J. S. Kate Brush, "chatbot," techtarget, 2021. https://www.techtarget.com/searchcustomerexperience/definition/ch atbot.
  40. Rocktechnolabs, "How Chatbot Benefits Your ECommerce Business," rocktechnolabs, 2021. https://rocktechnolabs.com/blog/ecommerce-chatbots-benefits/ (accessed May 27, 2022).
  41. L. Cui, S. Huang, F. Wei, C. Tan, C. Duan, and M. Zhou, "Superagent: A customer service chatbot for E-commerce websites," in ACL 2017 -55th Annual Meeting of the Association IEEE -54827 13th ICCCNT 2022 Oct 3-5, 2022 Virtual Conference Authorized licensed use limited to: UNIVERSITY PUTRA MALAYSIA. Downloaded on April 07,2023 at 13:25:27 UTC from IEEE Xplore. Restrictions apply. for Computational Linguistics, Proceedings of System Demonstrations, 2017, pp. 97-102, DOI: 10.18653/v1/P17-4017.
  42. A. Xu, Z. Liu, Y. Guo, V. Sinha, and R. Akkiraju, "A new chatbot for customer service on social media," in Conference on Human Factors in Computing Systems -Proceedings, May 2017, vol. 2017- May, pp. 3506-3510, DOI: 10.1145/3025453.3025496.
  43. A. Nursetyo, D. R. I. M. Setiadi, and E. R. Subhiyakto, "Smart chatbot system for E-commerce assistance based on AIML," 2018
  44. Int. Semin. Res. Inf. Technol. Intell. Syst. ISRITI 2018, pp. 641-645, 2018, doi: 10.1109/ISRITI.2018.8864349.
  45. U. Arsenijevic and M. Jovic, "Artificial Intelligence Marketing: Chatbots," in Proceedings -2019 International Conference on Artificial Intelligence: Applications and Innovations, IC-AIAI 2019, Sep. 2019, pp. 19-22, DOI: 10.1109/IC-AIAI48757.2019.00010.
  46. B. Wibowo, H. Clarissa, and D. Suhartono, "The Application of Chatbot for Customer Service in E-Commerce," 2020, [Online].
  47. Available: www.DeepDyve.com.
  48. M. M. Khan, "Development of An e-commerce Sales Chatbot," HONET 2020 -IEEE 17th Int. Conf. Smart Communities Improv. Qual. Life using ICT, IoT AI, pp. 173-176, 2020, DOI: 10.1109/HONET50430.2020.9322667.
  49. O. T. Tran and T. C. Luong, "Understanding what the users say in chatbots: A case study for the Vietnamese language," Eng. Appl. Artif. Intell., vol. 87, no. April 2019, p. 103322, 2020, doi: 10.1016/j.engappai.2019.103322.
  50. J. M. Solis-Quispe, K. M. Quico-Cauti, and W. Ugarte, "Chatbot to Simplify Customer Interaction in e-Commerce Channels of Retail Companies," 2021, pp. 561-570.
  51. V. Oguntosin and A. Oromo, "Development of an E-Commerce Chatbot for a University Shopping Mall," Appl. Comput. Intell. Soft Comput., vol. 2021, no. 1, 2021, DOI: 10.1155/2021/6630326.
  52. M. Chung, E. Ko, H. Joung, and S. J. Kim, "Chatbot e-service and customer satisfaction regarding luxury brands," J. Bus. Res., vol. 117, pp. 587-595, Sep. 2020, doi: 10.1016/j.jbusres.2018.10.004.
  53. Y. Cheng and H. Jiang, "Customer-brand relationship in the era of artificial intelligence: understanding the role of chatbot marketing efforts," J. Prod. Brand Manag., 2021, DOI: 10.1108/JPBM-05- 2020-2907.
  54. L. Lo Presti, G. Maggiore, and V. Marino, "The role of the chatbot on customer purchase intention: towards digital relational sales," Ital. J. Mark., vol. 2021, no. 3, pp. 165-188, Sep. 2021, doi: 10.1007/s43039-021-00029-6.

Related papers

Using Chatbots in Marketing Communication
Agnieszka Werenowska

Economic Sciences for Agribusiness and Rural Economy, 2020

The e-commerce industry is constantly growing and becoming a strong competition for stationary outlets. More and more e-stores are deciding to use new communication solutions. Many of them use so-called bots. The article presents the possibilities of using virtual assistants, the analysis of the literature on the subject and the results of conducted surveys on the use and familiarity of chatbots among recipients and managers. In the application of virtual assistants, managers see a chance to increase the possibility of effective communication with simultaneous reduction of the costs of carrying out this process. The benefits of this solution support the intensive and versatile use of it. At the same time, customers opt for direct contact with a consultant. That is why the perfect combination is to have both a chatbot and a real consultant.

View PDFchevron_right
Chatbot for digital marketing and customer support: an artificial intelligence approach
Humberto Vaz

2019

View PDFchevron_right
Artificial Machine Intelligence Conversation in Digital Marketing through Chatbots
Sushma Shetty

Zenodo (CERN European Organization for Nuclear Research), 2022

Chatbots are intelligent machines serving digital visitors.Intelligent machines are capable of simulating knowledge.This paper examines some of the latest AI patterns and activities then provides alternative theory of change in some of the popular and widely accepted postulates of today.Based on AI (Artificial Intelligence) structuring and NLP(Natural language Processing)based software, chatbots are made.The paper highlights that AI is ever improving and sheds light on the potential of machine intelligence and NLP tasks.The rise of chatbots in digital marketing is the latest disruptive force that led to a change in customer interaction.In the context of digital markets and digital services ,the emergence of AI driven chatbots has changed the phase of interaction among digital customers.The marketings sector plays an important role in development into any country.It also explores the usability of chatbots to assess whether it can fulfill digital customers ever-changing needs.

View PDFchevron_right
The role of chatbots in enhancing customer experience SESSION: 2024-26
Amisha Singh
View PDFchevron_right
Chatbots: A New Era of Digital Marketing
Hitesh Tikyani

2019

In today’s era, Digital Marketing is way ahead in comparison to other forms of marketing. One of the reasons is the usage of data. By observing customer’s interests, tastes, desires, etc. A lot of data is collected which allows marketers to take decisions regarding target marketing. Suppose, if you are looking for some footwear products on flipkart, the chances are that you will be seeing the ads of the same footwear products on maximum websites which you are going to visit in days coming. Businesses get this hint about your appeal towards their product and they chase you wherever and whatever you visit on internet. This is digital marketing.

View PDFchevron_right
580 California St., Suite 400
San Francisco, CA, 94104
© 2025 Academia. All rights reserved