KaydedilenlerDerginizi ekleyin

Dergiler / Pazarlama ve Pazarlama Araştırmaları Dergisi / 2026 / Cilt: 18 Sayı: 2

ÇEVRİMİÇİ ALIŞVERİŞTE MÜŞTERİ DENEYİMİ: YAPAY ZEKA DESTEKLİ ÜRÜN YORUMLARININ İÇERİK ANALİZİ İLE İNCELENMESİ

CUSTOMER EXPERIENCE IN ONLINE SHOPPING: CONTENT ANALYSIS OF ARTIFICIAL INTELLIGENCE-SUPPORTED PRODUCT REVIEWS

Aysun Varan(BEYKOZ ÜNİVERSİTESİ)0000-0001-6401-9542
Aslıhan Bekaroğlu Özatar(BEYKOZ ÜNİVERSİTESİ)0000-0002-5502-227X
Sayfa
459–480
Yayın Tarihi
2025-05-28
DOI
—
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Araştırmanın sonucunda, müşteri yorumlarının ürünün fiziksel kalitesi, dil destek özelliği, genel memnuniyet, ses algılama hızı ve ses kalitesi gibi somut unsurlara dayanan “Bilişsel Bilgi” ağırlıklı olduğu görülmektedir.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Yapay zeka, günlük hayatımıza giderek daha fazla dahil olmakta ve tüketicilerle sosyal medya, e-ticaret, eğlence, sağlık, kişisel asistanlar ve akıllı ev cihazları gibi çeşitli alanlarda buluşmaktadır.
📊
Temel Bulgular & Veri:Bu ürünlerin pazarı genişledikçe, online yorumlar aracılığıyla müşteri memnuniyetini değerlendirmek hem işletmeler hem de tüketiciler için giderek daha önemli olmaktadır.
💡
Sonuç & Katkı:Araştırmanın sonucunda, müşteri yorumlarının ürünün fiziksel kalitesi, dil destek özelliği, genel memnuniyet, ses algılama hızı ve ses kalitesi gibi somut unsurlara dayanan “Bilişsel Bilgi” ağırlıklı olduğu görülmektedir.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:yapay zeka · müşteri deneyimi · sesli asistan

Özet

Yapay zeka, günlük hayatımıza giderek daha fazla dahil olmakta ve tüketicilerle sosyal medya, e-ticaret, eğlence, sağlık, kişisel asistanlar ve akıllı ev cihazları gibi çeşitli alanlarda buluşmaktadır. Son yıllarda büyük bir popülerlik kazanan Akıllı Asistan Hoparlörler, dünya genelinde birçok tüketicinin evlerinde tercih ettiği bir ürün olmuştur. Bu ürünlerin pazarı genişledikçe, online yorumlar aracılığıyla müşteri memnuniyetini değerlendirmek hem işletmeler hem de tüketiciler için giderek daha önemli olmaktadır. Bu araştırmada, müşterilerin Akıllı Asistan Hoparlör seçimleriyle ilgili bilgi edinmek amacıyla online alışveriş sitelerindeki tüketici yorumları içerik analizi yöntemiyle incelenmiştir. Araştırmanın sonucunda, müşteri yorumlarının ürünün fiziksel kalitesi, dil destek özelliği, genel memnuniyet, ses algılama hızı ve ses kalitesi gibi somut unsurlara dayanan “Bilişsel Bilgi” ağırlıklı olduğu görülmektedir.

Abstract

Artificial intelligence is becoming increasingly involved in our daily lives, meeting consumers in a variety of areas such as social media, e-commerce, entertainment, healthcare, personal assistants and smart home devices. Smart Assistant Speakers, which have gained immense popularity in recent years, have become a preferred product in the homes of many consumers around the world. As the market for these products expands, assessing customer satisfaction through online reviews is increasingly important for both businesses and consumers. In this study, consumer reviews on online shopping sites were analyzed by content analysis method in order to obtain information about customers' Smart Assistant Speaker choices. As a result of the research, it is seen that customer reviews are predominantly based on “Cognitive Knowledge” based on concrete elements such as physical quality of the product, language support feature, general satisfaction, voice perception speed and voice quality.

🔖

Bu Makaleye Atıf Yap

Varan, A., Özatar, A. B. (2025). ÇEVRİMİÇİ ALIŞVERİŞTE MÜŞTERİ DENEYİMİ: YAPAY ZEKA DESTEKLİ ÜRÜN YORUMLARININ İÇERİK ANALİZİ İLE İNCELENMESİ. Pazarlama ve Pazarlama Araştırmaları Dergisi, Cilt: 18 Sayı: 2, 459–480. https://ajindex.com/articles/1301048

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (48)

  1. Acikgoz, F., Perez‐Vega, R., Okumus, F., & Stylos, N. (2023). Consumer engagement with AI‐powered voice assistants: A behavioral reasoning perspective. Psychology & Marketing, 40(11), 2226-2243. https://doi.org/10.1002/mar.21873
  2. Agapito, D. (2020). The senses in tourism design: A bibliometric review. Annals of Tourism Research, 83, Makale 102934. https://doi.org/10.1016/j.annals.2020.102934
  3. Aiolfi, S. (2023). How shopping habits change with artificial intelligence: smart speakers' usage intention. International Journal of Retail & Distribution Management, 51(9/10), 1288-1312. https://doi.org/10.1108/ijrdm-11-2022-0441
  4. Ameen, N., Tarhini, A., Reppel, A., & Anand, A. (2021). Customer experiences in the age of artificial intelligence. Computers in Human Behavior, 114, Makale 106548. https://doi.org/10.1016/j.chb.2020.106548
  5. Basha, M. (2023). Impact of artificial intelligence on marketing. East Asian Journal of Multidisciplinary Research, 2(3), 993-1004. https://doi.org/10.55927/eajmr.v2i3.3112
  6. Bornet, P., Barkin, I., & Wirtz, J. (2021). Intelligent automation: Welcome to the world of hyperautomation: learn how to harness artificial intelligence to boost business & make our world more human. Singapore: World Scientific Publishing https://doi.org/10.1142/9789811235849_0001
  7. Chintalapati, S., & Pandey, S. K. (2022). Artificial intelligence in marketing: A systematic literature review. International Journal of Market Research, 64(1), 38-68. https://doi.org/10.1177/14707853211018428
  8. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
  9. De Bruyn, A., Viswanathan, V., Beh, Y. S., Brock, J. K. U., & Von Wangenheim, F. (2020). Artificial intelligence and marketing: Pitfalls and opportunities. Journal of Interactive Marketing, 51(1), 91-105. https://doi.org/10.1016/j.intmar.2020.04.007
  10. De Keyser, A., Lemon, K. N., Klaus, P., & Keiningham, T. L. (2015). A framework for understanding and managing the customer experience. Marketing Science Institute working paper series, 85(1), 15-121.
  11. Guerreiro, J., & Loureiro, S. M. C. (2023). I am attracted to my cool smart assistant! Analyzing attachment-aversion in AI-human relationships. Journal of Business Research, 161, Makale 113863. https://doi.org/10.1016/j.jbusres.2023.113863
  12. Guha, A., Bressgott, T., Grewal, D., Mahr, D., Wetzels, M., & Schweiger, E. (2023). How artificiality and intelligence affect voice assistant evaluations. Journal of the Academy of Marketing Science, 51(4), 843-866. https://doi.org/10.1007/s11747-022-00874-7
  13. Hoch, S. J. (2002). Product experience is seductive. Journal of Consumer Research, 29(3), 448-454. https://doi.org/10.1086/344422
  14. Hoffman, D. L., & Novak, T. P. (2018). Consumer and object experience in the internet of things: An assemblage theory approach. Journal of Consumer Research, 44(6), 1178-1204. https://doi.org/10.1093/jcr/ucx105
  15. Holbrook, M. B., & Hirschman, E. C. (1982). The experiential aspects of consumption: Consumer fantasies, feelings, and fun. Journal of Consumer Research, 9(2), 132-140. https://doi.org/10.1086/208906
  16. Huang, M. H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49, 30-50. https://doi.org/10.1007/s11747-020-00749-9
  17. Huang, M. H., & Rust, R. T. (2022). A framework for collaborative artificial intelligence in marketing. Journal of Retailing, 98(2), 209-223. https://doi.org/10.1016/j.jretai.2021.03.001
  18. Jiménez-Barreto, J., Rubio, N., Mura, P., Sthapit, E., & Campo, S. (2023). “Ask Google Assistant where to travel” tourists’ interactive experiences with smart speakers: An assemblage theory approach. Journal of Travel Research, 62(4), 734-752. https://doi.org/10.1177/00472875221094073
  19. Jones, V. K. (2018). Voice-activated change: Marketing in the age of artificial intelligence and virtual assistants. Journal of Brand Strategy, 7(3), 233-245. https://doi.org/10.69554/WUQT4128
  20. Kim, D., & Perdue, R. R. (2013). The effects of cognitive, affective, and sensory attributes on hotel choice. International Journal of Hospitality Management, 35, 246-257. https://doi.org/10.1016/j.ijhm.2013.05.012
  21. Kshetri, N., Dwivedi, Y. K., Davenport, T. H., & Panteli, N. (2024). Generative artificial intelligence in marketing: Applications, opportunities, challenges, and research agenda. International Journal of Information Management, 75, Makale 102716. https://doi.org/10.1016/j.ijinfomgt.2023.102716
  22. Krishna, A., & Schwarz, N. (2014). Sensory marketing, embodiment, and grounded cognition: A review and introduction. Journal of consumer psychology, 24(2), 159-168. https://doi.org/10.1016/j.jcps.2013.12.006
  23. Krippendorff, K. (2004). Content Analysis An Introduction to Its Methodology. California: Sage Publications, Inc.
  24. Kumar, V., Rajan, B., Venkatesan, R., & Lecinski, J. (2019). Understanding the role of artificial intelligence in personalized engagement marketing. California Management Review, 61(4), 135-155. https://doi.org/10.1177/0008125619859317
  25. Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 159-174. https://doi.org/10.2307/2529310
  26. Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, 80(6), 69-96. https://doi.org/10.1509/jm.15.0420
  27. Li, L., Lee, K. Y., Emokpae, E., ve Yang, S. B. (2021). What makes you continuously use chatbot services? Evidence from Chinese online travel agencies. Electronic Markets, 31(4), 757–781. https://doi.org/10.1007/s12525-020-00454-z
  28. Lv, X., & McCabe, S. (2020). Expanding theory of tourists’ destination loyalty: The role of sensory impressions. Tourism Management, 77, Makale 104026. https://doi.org/10.1016/j.tourman.2019.104026
  29. Malodia, S., Ferraris, A., Sakashita, M., Dhir, A., & Gavurova, B. (2023). Can Alexa serve customers better? AI-driven voice assistant service interactions. Journal of Services Marketing, 37(1), 25-39. https://doi.org/10.1108/JSM-12-2021-0488
  30. Mari, A., Mandelli, A., & Algesheimer, R. (2024). Empathic voice assistants: Enhancing consumer responses in voice commerce. Journal of Business Research, 175, Makale 114566. https://doi.org/10.1016/j.jbusres.2024.114566
  31. Mariani, M. M., Hashemi, N., & Wirtz, J. (2023). Artificial intelligence empowered conversational agents: A systematic literature review and research agenda. Journal of Business Research, 161, Makale 113838. x https://doi.org/10.1016/j.jbusres.2023.113838
  32. McLean, G., Osei-Frimpong, K., & Barhorst, J. (2021). Alexa, do voice assistants influence consumer brand engagement? Examining the role of ai powered voice Assistants in Influencing Consumer Brand Engagement. Journal of Business Research, 124, 312-328 https://doi.org/10.1016/j.jbusres.2020.11.045
  33. Novak, T. P. & Hoffman, D. L. (2019). Relationship journeys in the internet of things: a new framework for understanding interactions between consumers and smart objects. Journal of the Academy of Marketing Science, 47, 216-237. https://doi.org/10.1007/s11747-018-0608-3
  34. Rohit, K., Shankar, A., Katiyar, G., Mehrotra, A., & Alzeiby, E. A. (2024). Consumer engagement in chatbots and voicebots. A multiple-experiment approach in online retailing context. Journal of Retailing and Consumer Services, 78, Makale 103728. https://doi.org/10.1016/j.jretconser.2024.103728
  35. Rosário, A. (2021). The Background of artificial intelligence applied to marketing. Academy of Strategic Management Journal, 20(6), 1-19. https://doi.org/1939-6104-20-S6-118
  36. Pappas, A., Fumagalli, E., Rouziou, M., & Bolander, W. (2023). More than machines: The role of the future retail salesperson in enhancing the customer experience. Journal of Retailing, 99(4), 518-531. https://doi.org/10.1016/j.jretai.2023.10.004
  37. Peruchini, M., da Silva, G. M., & Teixeira, J. M. (2024). Between artificial intelligence and customer experience: a literature review on the intersection. Discover Artificial Intelligence, 4(1), Makal, 4. https://doi.org/10.1007/s44163-024-00105-8
  38. Pine, B. J., & Gilmore, J. H. (1998). Welcome to the experience economy. Harvard Business Review, 76(4), 97-105.
  39. Pitardi, V., & Marriott, H. R. (2021). Alexa, she’s not human but. unveiling the drivers of consumers’ trust in voice-based artificial intelligence. Psychology & Marketing, 38(4), 626-642. https://doi.org/10.1002/mar.21457
  40. Schmitt, B. (1999). Experiential marketing. Journal of Marketing Management, 15(1-3), 53-67. https://doi.org/10.1362/026725799784870496
  41. Schmitt, B., & Zarantonello, L. (2013). Consumer experience and experiential marketing: A critical review. Review of Marketing Research, 25-61. https://doi.org/10.1108/S1548-6435(2013)0000010006
  42. Statista. (2022). Installed base of smart speakers worldwide in 2020 and 2024. https://www.statista.com/statistics/878650/worldwide-smart-speaker-installed-base-by-country/, Erişim 27.03.2024
  43. Van Kleef, G. A. (2010). The emerging view of emotion as social information. Social and Personality Psychology Compass, 4(5), 331-343. https://doi.org/10.1111/j.1751-9004.2010.00262.x
  44. Wang, F., Du, Z., & Wang, S. (2023). Information multidimensionality in online customer reviews. Journal of Business Research, 159 Makale113727. https://doi.org/10.1016/j.jbusres.2023.113727
  45. Wirtz, J., Patterson, P. G., Kunz, W. H., Gruber, T., Lu, V. N., Paluch, S., & Martins, A. (2018). Brave new world: service robots in the frontline. Journal of Service Management, 29(5), 907-931 https://doi.org/10.1108/JOSM-04-2018-0119
  46. Yang, B., Liu, Y., Liang, Y., & Tang, M. (2019). Exploiting user experience from online customer reviews for product design. International Journal of Information Management, 46, 173-186. https://doi.org/10.1016/j.ijinfomgt.2018.12.006
  47. Krippendorff, K. (2004). Content Analysis An Introduction to Its Methodology. California: Sage Publications, Inc.
  48. Pitardi, V., & Marriott, H. R. (2021). Alexa, she’s not human but. unveiling the drivers of consumers’ trust in voice-based artificial intelligence. Psychology & Marketing, 38(4), 626-642. https://doi.org/10.1002/mar.21457