SANAL MÜŞTERİ ASİSTANLARI CHATBOTLARA YÖNELİK TÜKETİCİ DÜŞÜNCELERİ VE ŞİKAYETLERİ

Year 2025, Volume: 10 Issue: 2, 518 - 530, 12.12.2025

Deniz Özer Alper

https://doi.org/10.54452/jrb.1701815

Abstract

Chatbotlar yapay zeka ve doğal dil işleme teknolojileri kullanarak müşteri sorularına hızlı ve etkili yanıtlar verebilen sanal müşteri hizmetleri asistanlardır. Bazı araştırmalar chatbotların müşteri hizmetleri süreçlerini hızlandırdığı ve operasyonel maliyetleri düşürdüğü yönünde bulgular sunmaktadır. Ancak tüketici güveni ve memnuniyeti üzerindeki etkileri konusunda farklı görüşler bulunmaktadır. Bazı çalışmalar da chatbotların samimiyetten uzak ve mekanik yanıtlar vermesinin tüketici güvenini zedeleyebileceğini öne sürmekteyken; diğerleri hızlı çözüm sunma kapasitelerinin memnuniyeti artırabileceğini savunmaktadır. Bu araştırma chatbotların etkinliğini incelemek amacıyla nitel bir yöntem benimsemiştir. Çalışma kapsamında şikayet sitelerinde belirli markaların chatbot uygulamaları hakkındaki şikayetleri analiz edilmiş ve kullanıcı yorumları içerik analizi ile incelenmiştir. Elde edilen bulgular chatbotların şikayet yönetimi süreçlerinde önemli bir araç olduğunu; ancak tek başına yeterli olmadığını ortaya koymaktadır. Chatbotların etkinliği, kullanılan teknolojinin gelişmişliği ve yanıtların kişiselleştirilme düzeyine bağlı olmaktadır. Tüketici güvenini sağlamak için chatbotlar ile insan müşteri temsilcilerinin entegre bir şekilde çalışması önerilmektedir.

Keywords

Chatbot , Tüketici güveni , Tüketici memnuniyeti , Şikayet siteleri , Müşteri hizmetleri

CONSUMER OPINIONS AND COMPLAINTS REGARDING VIRTUAL CUSTOMER ASSISTANTS (CHATBOTS)

Abstract

Chatbots are virtual customer service assistants that utilize artificial intelligence and natural language processing technologies to provide fast and effective responses to customer inquiries. Several studies indicate that chatbots accelerate customer service processes and reduce operational costs. However, there are divergent views regarding their impact on consumer trust and satisfaction. While some research suggests that the impersonal and mechanical nature of chatbot responses may undermine consumer trust, others argue that their capacity to offer quick solutions can enhance satisfaction. This study adopts a qualitative approach to examine the effectiveness of chatbots. Within the scope of the research, complaints about specific brands’ chatbot applications posted on complaint websites were analyzed through content analysis of user comments. The findings reveal that while chatbots serve as a significant tool in complaint management processes, they are not sufficient on their own. The effectiveness of chatbots depends on the sophistication of the technology employed and the degree of personalization in the responses. To foster consumer trust, it is recommended that chatbots operate in integration with human customer service agents.

Keywords

Chatbot , Consumer trust , Customer satisfactions , Complaint websites , Customer service

References

• Abraham, C. L., Nihdin, V. R., Nair, N, P., & Venugopal, P. (2025) Consumer Perception on the Effectiveness of Chatbot. In: Fong, S., Dey, N., Joshi, A. (eds) ICT Analysis and Applications. ICT4SD. Lecture Notes in Networks and Systems, vol 1161. p. 81-89. Springer, Singapore. https://doi.org/10.1007/978-981-97- 8602-2_8
• Acayıp, E., (2024). Yapay zeka destekli chatbot hizmet kalitesinin müşteri memnuniyetine etkisi. Current Perspectives in Social Sciences, 28 (4), 477-490.
• Adamopoulou, E., & Moussiades, L. (2020). An overview of chatbot technology. In: Maglogiannis, I., Iliadis, L., Pimenidis, E. (eds) Artificial Intelligence Applications and Innovations. IFIP Advances in Information and Communication Technology. 584, pp. 373–383. Springer, Cham.
• Brandtzaeg, P., & Følstad, A. (2017). Why people use chatbots. Internet Science. INSCI 2017, (pp. 377–392).
• Coombs, W. T. (2007). Ongoing crisis communication: Planning, managing, and responding. Thousand Oaks, CA: Sage Publications.
• Følstad, A., & Brandtzaeg, P. B. (2017). Chatbots and the new world of HCI . Interactions , 24 (4), 38-42.
• Fota, A., Wagner, K., Rödig, T., & Schramm-Klein, H. (2022). “Help! I have a Ppoblem” – Differences between a humanlike and robot-like chatbot avatar in complaint management. Proceedings of the 55th Hawaii International Conference on System Sciences, (pp. 4273-4282).
• Gnewuch, U., Morana, S., & Mädche, A. (2017). Towards designing cooperative and social conversational agents for customer service. Proceedings of the International Conference on Information Systems (ICIS) , 1-19.
• Grunig, J., & Hunt, T. (1984). Managing public relations.
• Jang, Y. (2020). Exploring user interaction and satisfaction with virtual personal assistant usage through smart speakers. Archives of Design Research , 33 (3), 127-134.
• Janson, A. (2023). How to leverage anthropomorphism for chatbot service interfaces: The interplay of communication style and personification . Computers in Human Behavior , 149 (1), 1-17.
• Le, T. P., & Rajah, E. (2022). Using chatbots in customer service: A case study of Air New Zaland. Proceedings: Rangahau Horonuku Hou – New Research Landscapes, Unitec/MIT Research Symposium 2021, (pp. 161- 176). Auckland: ePress, Unitec, Te Pūkenga.
• Luger, E., & Sellen, A. (2016). “Like having a really bad PA”: The Gulf between user expectation and experience of conversational agents. CHI ‘16: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems , (pp. 5286 – 5297).
• McTear, M. F. (2016). The rise of the conversational interface: A new kid on the block? Future and emerging trends in language technology. Machine Learning and Big Data, (pp. 38-48).
• Taddeo, M., & Floridi, L. (2018). How AI can be a force for good. Perspectives , 751-752.
• Tran, A. D., Pallant, J. I., & Johnson, L. W. (2021). Exploring the impact of chatbots on consumer sentiment and expectations in retail. Journal of Retailing and Consumer Services. 63. https://doi.org/10.1016/j. jretconser.2021.102718
• Xing, X., Song, M., Duan, Y. & Mou, J. (2022). Effects of different service failure types and recovery strategies on the consumer response mechanism of chatbots. Technology in Society. 70. https://doi.org/10.1016/j. techsoc.2022.102049