Araştırma Makalesi
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KULLANICILARIN MARKALI İÇERİKLERE VE DOĞAL REKLAMLARA YÖNELİK ONLİNE DAVRANIŞSAL TEPKİLERİNİN WEB ANALİTİK ARAÇLARI ARACILIĞIYLA DEĞERLENDİRİLMESİ

Yıl 2025, Cilt: 10 Sayı: 2, 557 - 577, 12.12.2025
https://doi.org/10.47107/inifedergi.1736661

Öz

Bu çalışma, kullanıcıların markalı içeriklere ve doğal reklam uygulamalarına yönelik online davranışsal tepkilerini web analitik araçları aracılığıyla değerlendirmeyi amaçlamaktadır. Bu amaçla planlanan bir araştırma projesi kapsamında öncelikle, araştırmaya özgü bir web sitesi, hayali bir marka, reklam uyaranları ve ilgili diğer içerikler tasarlanmıştır. Söz konusu içerikler, deneysel uyaranlar olarak web sitesi ortamında katılımcılara sunulmuş; sitede gezinme deneyimi yaşayan kullanıcıların online davranışları web analitik araçları aracılığıyla izlenmiştir. Araştırmanın üniversite öğrencilerinden oluşan bir örneklem üzerinde uygulanması planlanmıştır. Örneklemin deneysel uyaranların içeriği ve bağlamına yönelik ilginliği kriteri göz önünde bulundurularak web sitesi “yurt dışı eğitim olanakları” konusunda; reklamveren marka ise ilgili alanda bir “eğitim danışmanlık şirketi” olarak kurgulanmıştır. Kullanıcıların online davranışsal tepkileri Google Analytics, Yandex Metrica ve Microsoft Clarity araçlarıyla izlenmiş ve analiz edilmiştir. Söz konusu analitik araçları aracılığıyla; ziyaretçilerin sayfaları ve içerikleri görüntüleme süreleri, tıklama davranışları ve diğer etkileşimleri, temel analitik metrikleri, oturum kaydı ve ısı haritası teknikleri ile incelenmiştir. Sonuç olarak, gerçekçi bir medya kullanım deneyimi yaratarak, uygun bağlama yerleştirilen markalı içeriklere ve reklamlara yönelik kullanıcı davranışlarına dair bulgular elde edilmiştir. Kullanıcıların organik olarak sunulan içeriklere, sponsorlu olarak etiketlenen içeriklere kıyasla daha fazla ilgi gösterdiği; bununla birlikte medya tüketim deneyimini kesintiye uğratmayan ya da rahatsız edici biçimde araya girmeyen doğal reklamların, banner biçimli reklamlara kıyasla daha olumlu tepkiler elde ettiği görülmüştür. Bu çalışma, incelenen pazarlama iletişimi uygulamalarına yönelik bulgularıyla gerek akademi gerek uygulama alanına yönelik çıkarımlar sunmanın yanı sıra, akademik araştırmalarda nadir olarak kullanılan bir araştırma yöntemine başvurarak yenilikçi bir yaklaşım ve buna uygun çıktılar sunmaktadır.

Destekleyen Kurum

Anadolu Üniversitesi

Proje Numarası

YTS-2024-2391

Teşekkür

Yazar, Anadolu Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimine proje desteği için teşekkür eder.

Kaynakça

  • Benway, J. P. (1998). Banner blindness: The irony of attention grabbing on the World Wide Web. In Proceedings of the human factors and ergonomics society annual meeting (Vol. 42, No. 5, pp. 463-467). Los Angeles, CA: Sage Publications.
  • Burby, J., Brown, A., and WAA Standards Committee. (2007). Web analytics definitions. Washington DC: Web Analytics Association.
  • CMI. (2023). https://contentmarketinginstitute.com/what-is-content-marketing/, (Erişim Tarihi: 02.12.2023)
  • Das, S., Soni, A., Venkatesan, A., and Donato, D. (2015). Organic vs. sponsored content: From ads to native ads. In 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) (Vol. 3, pp. 229-230). IEEE.
  • De Keyzer, F., Dens, N., and De Pelsmacker, P. (2023). The processing of native advertising compared to banner advertising: an eye-tracking experiment. Electronic Commerce Research, 23(3), 1921-1940.
  • Friestad, M., and Wright, P. (1994). The persuasion knowledge model: How people cope with persuasion attempts. Journal of Consumer Research, 21(1), 1-31.
  • Geuens, M., and De Pelsmacker, P. (2017). Planning and conducting experimental advertising research and questionnaire design. Journal of Advertising, 46(1), 83-100.
  • Gülmez, E. ve Akarsu, H. (2019). Reklam araştırmalarında web analitik kullanımı. G. Şener ve S. Yıldız (Ed.), İletişim araştırmalarında farklı bakış açıları, (s. 121-151). Ankara: Detay Yayıncılık.
  • Harms, B., Bijmolt, T. H., and Hoekstra, J. C. (2017). Digital native advertising: Practitioner perspectives and a research agenda. Journal of Interactive Advertising, 17(2), 80-91.
  • Hervet, G., Guérard, K., Tremblay, S., and Chtourou, M. S. (2011). Is banner blindness genuine? Eye tracking internet text advertising. Applied Cognitive Psychology, 25(5), 708-716.
  • IAB. (2016). IAB Doğal (Native) Reklam Oyun Kitabı. https://iabtr.org/UploadFiles/Reports/iab_dogal_reklam_oyun_kitabi05072017172639.pdf
  • IAB. (2019). IAB Native Advertising Playbook 2.0. https://www.iab.com/wp-content/uploads/2019/05/IAB-Native-Advertising-Playbook-2_0_Final.pdf
  • Järvinen, J., and Karjaluoto, H. (2015). The use of Web analytics for digital marketing performance measurement. Industrial Marketing Management, 50, 117-127.
  • Karpinska-Krakowiak, M., and Modlinski, A. (2020). Popularity of branded content in social media. Journal of Computer Information Systems, 60(4), 309-315.
  • Kim, M., and Song, D. (2017). When brand-related UGC induces effectiveness on social media: the role of content sponsorship and content type. International Journal of Advertising, 37(1), 105–124.
  • Kim, S., Youn, S., and Yoon, D. (2019). Consumers’ responses to native vs. banner advertising: moderation of persuasion knowledge on interaction effects of ad type and placement type. International Journal of Advertising, 38(2), 207-236.
  • LaBrecque, A. C., Voorhees, C. M., Khodakarami, F., and Fombelle, P. W. (2024). Native advertising effectiveness: The role of congruence and consumer annoyance on clicks, bounces, and visits. Journal of the Academy of Marketing Science, 52(6), 1692-1712.
  • Lieb, R. (2012). Content marketing: Think like a publisher-How to use content to market online and in social media. Indiana: Que Publishing.
  • Lou, C., Xie, Q., Feng, Y., and Kim, W. (2019). Does non-hard-sell content really work? Leveraging the value of branded content marketing in brand building. Journal of Product & Brand Management, 28(7), 773-786.
  • Maintz, J., and Zaumseil, F. (2019). Tracking content marketing performance using web analytics: tools, metrics, and data privacy implications. International Journal of Internet Marketing and Advertising, 13(2), 170-182.
  • McGuirk, M. (2023). Performing web analytics with Google Analytics 4: A platform review. Journal of Marketing Analytics, 11(4), 854-868.
  • Morales A. C., Amir O., and Lee L. (2017). Keeping it real in experimental research-understanding when, where, and how to enhance realism and measure consumer behavior. Journal of Consumer Research, 44(2), 465-476.
  • Pakkala, H., Presser, K., and Christensen, T. (2012). Using Google Analytics to measure visitor statistics: The case of food composition websites. International Journal of Information Management, 32(6), 504-512.
  • Plaza, B. (2011). Google Analytics for measuring website performance. Tourism Management, 32(3), 477-481.
  • Pulizzi, J., and Barrett, N. (2009). Get content get customers: Turn prospects into buyers with content marketing. USA: McGraw-Hill.
  • Stubb, C. (2018). Story versus info: Tracking blog readers’ online viewing time of sponsored blog posts based on content-specific elements. Computers in Human Behavior, 82, 54-62.
  • Taylor, C. R. (2017). Native advertising: The black sheep of the marketing family. International Journal of Advertising, 36(2), 207-209.
  • Wang, J., and Calder, B. J. (2006). Media transportation and advertising. Journal of Consumer Research, 33(2), 151-162.
  • Waqas, M., Salleh, N. A. M., and Hamzah, Z. L. (2021). Branded content experience in social media: Conceptualization, scale development, and validation. Journal of Interactive Marketing, 56(1), 106-120.
  • Wojdynski, B. W., and Evans, N. J. (2016). Going native: Effects of disclosure position and language on the recognition and evaluation of online native advertising. Journal of Advertising, 45(2), 157-168.
  • Yıldız, S. and Sever, N. S. (2022). Investigating the Effects of Narrative Advertising in a Real-Life Setting. International Journal of Market Research, 64(4) 541–559.

EVALUATION OF USERS’ ONLINE BEHAVIORAL RESPONSES TOWARDS BRANDED CONTENT AND NATIVE ADVERTISING THROUGH WEB ANALYTICS TOOLS

Yıl 2025, Cilt: 10 Sayı: 2, 557 - 577, 12.12.2025
https://doi.org/10.47107/inifedergi.1736661

Öz

This study aims to evaluate users' online behavioral responses to branded content and native advertising using web analytics tools. Within the scope of a research project planned for this purpose, a research-specific website, a fictitious brand, advertising stimuli, and other related content were designed. The participants browsed the website content as experimental stimuli, and web analytics tools monitored their online behaviors. The research targeted a sample consisting of university students. Considering the criterion of relevance of the sample to the content and context of the experimental stimuli, the website focused on "study abroad opportunities," while the advertiser brand was designed as an "education consultancy company." Users' online behavioral responses were monitored and analyzed using Google Analytics, Yandex Metrica, and Microsoft Clarity tools. These analytics tools allowed for the examination of visitors' page and content viewing durations, click behaviors, and other interactions through basic analytics metrics, session recordings, and heatmap techniques. As a result, the research provided findings about user behavior towards branded content and advertisements placed in appropriate contexts by creating a realistic media usage experience. Results indicated that users showed greater interest in organic content compared to content labeled as sponsored; however, native advertisements that do not interrupt or intrude on the media experience elicited more positive responses than banner ads. This study provides both academic and practical implications based on its findings regarding the marketing communication practices. The study also presents an innovative approach and related outputs by applying a research method that is rarely used in academic research.

Destekleyen Kurum

Anadolu University

Proje Numarası

YTS-2024-2391

Teşekkür

The author would like to thank Anadolu University Scientific Research Projects Coordination Office for the project support.

Kaynakça

  • Benway, J. P. (1998). Banner blindness: The irony of attention grabbing on the World Wide Web. In Proceedings of the human factors and ergonomics society annual meeting (Vol. 42, No. 5, pp. 463-467). Los Angeles, CA: Sage Publications.
  • Burby, J., Brown, A., and WAA Standards Committee. (2007). Web analytics definitions. Washington DC: Web Analytics Association.
  • CMI. (2023). https://contentmarketinginstitute.com/what-is-content-marketing/, (Erişim Tarihi: 02.12.2023)
  • Das, S., Soni, A., Venkatesan, A., and Donato, D. (2015). Organic vs. sponsored content: From ads to native ads. In 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) (Vol. 3, pp. 229-230). IEEE.
  • De Keyzer, F., Dens, N., and De Pelsmacker, P. (2023). The processing of native advertising compared to banner advertising: an eye-tracking experiment. Electronic Commerce Research, 23(3), 1921-1940.
  • Friestad, M., and Wright, P. (1994). The persuasion knowledge model: How people cope with persuasion attempts. Journal of Consumer Research, 21(1), 1-31.
  • Geuens, M., and De Pelsmacker, P. (2017). Planning and conducting experimental advertising research and questionnaire design. Journal of Advertising, 46(1), 83-100.
  • Gülmez, E. ve Akarsu, H. (2019). Reklam araştırmalarında web analitik kullanımı. G. Şener ve S. Yıldız (Ed.), İletişim araştırmalarında farklı bakış açıları, (s. 121-151). Ankara: Detay Yayıncılık.
  • Harms, B., Bijmolt, T. H., and Hoekstra, J. C. (2017). Digital native advertising: Practitioner perspectives and a research agenda. Journal of Interactive Advertising, 17(2), 80-91.
  • Hervet, G., Guérard, K., Tremblay, S., and Chtourou, M. S. (2011). Is banner blindness genuine? Eye tracking internet text advertising. Applied Cognitive Psychology, 25(5), 708-716.
  • IAB. (2016). IAB Doğal (Native) Reklam Oyun Kitabı. https://iabtr.org/UploadFiles/Reports/iab_dogal_reklam_oyun_kitabi05072017172639.pdf
  • IAB. (2019). IAB Native Advertising Playbook 2.0. https://www.iab.com/wp-content/uploads/2019/05/IAB-Native-Advertising-Playbook-2_0_Final.pdf
  • Järvinen, J., and Karjaluoto, H. (2015). The use of Web analytics for digital marketing performance measurement. Industrial Marketing Management, 50, 117-127.
  • Karpinska-Krakowiak, M., and Modlinski, A. (2020). Popularity of branded content in social media. Journal of Computer Information Systems, 60(4), 309-315.
  • Kim, M., and Song, D. (2017). When brand-related UGC induces effectiveness on social media: the role of content sponsorship and content type. International Journal of Advertising, 37(1), 105–124.
  • Kim, S., Youn, S., and Yoon, D. (2019). Consumers’ responses to native vs. banner advertising: moderation of persuasion knowledge on interaction effects of ad type and placement type. International Journal of Advertising, 38(2), 207-236.
  • LaBrecque, A. C., Voorhees, C. M., Khodakarami, F., and Fombelle, P. W. (2024). Native advertising effectiveness: The role of congruence and consumer annoyance on clicks, bounces, and visits. Journal of the Academy of Marketing Science, 52(6), 1692-1712.
  • Lieb, R. (2012). Content marketing: Think like a publisher-How to use content to market online and in social media. Indiana: Que Publishing.
  • Lou, C., Xie, Q., Feng, Y., and Kim, W. (2019). Does non-hard-sell content really work? Leveraging the value of branded content marketing in brand building. Journal of Product & Brand Management, 28(7), 773-786.
  • Maintz, J., and Zaumseil, F. (2019). Tracking content marketing performance using web analytics: tools, metrics, and data privacy implications. International Journal of Internet Marketing and Advertising, 13(2), 170-182.
  • McGuirk, M. (2023). Performing web analytics with Google Analytics 4: A platform review. Journal of Marketing Analytics, 11(4), 854-868.
  • Morales A. C., Amir O., and Lee L. (2017). Keeping it real in experimental research-understanding when, where, and how to enhance realism and measure consumer behavior. Journal of Consumer Research, 44(2), 465-476.
  • Pakkala, H., Presser, K., and Christensen, T. (2012). Using Google Analytics to measure visitor statistics: The case of food composition websites. International Journal of Information Management, 32(6), 504-512.
  • Plaza, B. (2011). Google Analytics for measuring website performance. Tourism Management, 32(3), 477-481.
  • Pulizzi, J., and Barrett, N. (2009). Get content get customers: Turn prospects into buyers with content marketing. USA: McGraw-Hill.
  • Stubb, C. (2018). Story versus info: Tracking blog readers’ online viewing time of sponsored blog posts based on content-specific elements. Computers in Human Behavior, 82, 54-62.
  • Taylor, C. R. (2017). Native advertising: The black sheep of the marketing family. International Journal of Advertising, 36(2), 207-209.
  • Wang, J., and Calder, B. J. (2006). Media transportation and advertising. Journal of Consumer Research, 33(2), 151-162.
  • Waqas, M., Salleh, N. A. M., and Hamzah, Z. L. (2021). Branded content experience in social media: Conceptualization, scale development, and validation. Journal of Interactive Marketing, 56(1), 106-120.
  • Wojdynski, B. W., and Evans, N. J. (2016). Going native: Effects of disclosure position and language on the recognition and evaluation of online native advertising. Journal of Advertising, 45(2), 157-168.
  • Yıldız, S. and Sever, N. S. (2022). Investigating the Effects of Narrative Advertising in a Real-Life Setting. International Journal of Market Research, 64(4) 541–559.
Toplam 31 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Dijital Reklamcılık, Reklam Araştırmaları
Bölüm Araştırma Makalesi
Yazarlar

Serdar Yıldız 0000-0002-1565-3552

Proje Numarası YTS-2024-2391
Gönderilme Tarihi 8 Temmuz 2025
Kabul Tarihi 30 Eylül 2025
Yayımlanma Tarihi 12 Aralık 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 10 Sayı: 2

Kaynak Göster

APA Yıldız, S. (2025). KULLANICILARIN MARKALI İÇERİKLERE VE DOĞAL REKLAMLARA YÖNELİK ONLİNE DAVRANIŞSAL TEPKİLERİNİN WEB ANALİTİK ARAÇLARI ARACILIĞIYLA DEĞERLENDİRİLMESİ. İnönü Üniversitesi İletişim Fakültesi Elektronik Dergisi (İNİF E-Dergi), 10(2), 557-577. https://doi.org/10.47107/inifedergi.1736661