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Nano, Micro, Mid-Tier, Macro, Mega: The Relationship between the Influencer Type and Efficiency of Collaboration Ads in Digital Marketing

Yıl 2024, Sayı: 41, 76 - 103, 29.12.2024

Naim Çetintürk

https://doi.org/10.16878/gsuilet.1420953

Öz

This study aims to understand the relationship between the type of influencer and various efficiency factors based on the number of followers. Data from 1209 Turkish influencers were analyzed using descriptive statistics, multiple regression, and variance analyses. Descriptive statistics indicate that nano influencers, who have the fewest followers, exhibit significantly higher organic engagement compared to other influencers. Conversely, as the number of followers increases in paid advertising posts, the interaction rate decreases. Multiple regression analysis reveals a significant relationship between influencer type, post type (paid/organic), and engagement rate. Additionally, the interaction rate is associated with cost per person (CPP) and cost per sales (CPS), factors previously unaddressed in past studies. The results of the two-way variance analysis demonstrate a strong differentiation between the engagement ratios of different influencer types and post types.

Anahtar Kelimeler

Influencer digital marketing advertising e-commerce social media

Kaynakça

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  • Boerman, S. C. (2020). The effects of the standardized Instagram disclosure for micro-and meso-influencers. Computers in human behavior, 103, s. 199-207.
  • Boerman, S. C., Meijers, M. H., ve Zwart, W. (2022). The importance of influencer-message congruence when employing greenfluencers to promote pro-environmental behavior. Environmental Communication, 16(7), s. 920-941.
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  • Brown, D., ve Hayes, N. (2008). Influencer marketing. Routledge.
  • Bu, Y. P., ve Thaichon, P. (2022). Influencer marketing: sponsorship disclosure and value co-creation behaviour. Marketing Intelligence & Planning, 40(7), s. 854-870.
  • Campbell, C., ve Farrell, J. R. (2020). More than meets the eye: The functional components underlying influencer marketing. Business horizons, 63(4), s. 469-479.
  • Campbell, M. C., ve Kirmani, A. (2000). Consumers' use of persuasion knowledge: The effects of accessibility and cognitive capacity on perceptions of an influence agent. Journal of consumer research, 27(1), s. 69-83.
  • Carman, A. (2024). Paid Impact on Organic.Adjust. Erişim 04.06.2024, https://www.adjust.com/blog/paid-impact-on-organic/
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  • Chung, Y. J., Lee, S. S., ve Kim, E. (2023). The effects of influencer types and sponsorship disclosure in instagram sponsored posts. Journal of Current Issues & Research in Advertising, 44(2), s. 193-211.
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  • Evans, D. (2010). Social Media Marketing: The Next Generation of Business Engagement. Wiley.
  • Farivar, S., Wang, F., ve Yuan, Y. (2021). Opinion leadership vs. para-social relationship: Key factors in influencer marketing. Journal of Retailing and Consumer Services, 59.
  • Fenomio. (2023). Erişim 16.09.2023, https://www.fenomio.com
  • Field, A. (2005). Discovering statistics using SPSS for windows: Advanced techniques for beginners. Sage Publications.
  • Friestad, M., ve Wright, P. (1994). The persuasion knowledge model: How people cope with persuasion attempts. Journal of consumer research, 21(1), s. 1-31.
  • Gan, T., Wang, S., Liu, M., Song, X., Yao, Y., ve Nie, L. (2019). Seeking micro-influencers for brand promotion. Proceedings of the 27th ACM International Conference on Multimedia, s. 1933-1941.
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  • Goward, C. (2012). You Should Test That: Conversion Optimization for More Leads, Sales and Profit or The Art and Science of Optimized Marketing. John Wiley & Sons.
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Nano, Micro, Mid-Tier, Macro, Mega : La Relation Entre Le Type D'influenceur Et L'efficacité Des Publicités Collaboratives Dans Le Marketing Numérique

Yıl 2024, Sayı: 41, 76 - 103, 29.12.2024

Naim Çetintürk

https://doi.org/10.16878/gsuilet.1420953

Öz

Cette étude vise à comprendre la relation entre le type d'influenceur et plusieurs facteurs d'efficacité basés sur le nombre d'abonnés. Les données provenant de 1209 influenceurs turcs ont été examinées à l'aide de statistiques descriptives, de régressions multiples et d'analyses de variance. Les statistiques descriptives indiquent que les nano-influenceurs, avec le moins d'abonnés, ont un taux d'engagement organique significativement plus élevé par rapport aux autres, et à mesure que le nombre d'abonnés augmente dans les publications publicitaires payées, le taux d'interaction diminue. L'analyse de régression multiple révèle une relation significative entre le type d'influenceur, le type de publication (payée/organique) et le taux d'engagement. Le taux d'interaction est également associé au coût par personne (CPP) et au coût par vente (CPS), des facteurs non pris en compte dans les études antérieures. Les résultats de l'analyse de variance à deux facteurs démontrent une forte différenciation entre les taux d'engagement en fonction du type d'influenceur et du type de publication.

Anahtar Kelimeler

Influenceur marketing numérique publicité commerce électronique réseaux sociaux

Kaynakça

  • AgencyAnalytics. (2020). Followers vs. Following Ratios. Erişim 01.06.2024, https://www.pathsocial.com/resources/followers-vs-following-ratios-impact-on-instagram/ Aizen, E. (2023). Four Tips for Nano Influencers. Fast Company. Erişim 04.06.2024 https://www.fastcompany.com/90969738/4-tips-for-nano-influencers-looking-to-land-lucrative-partnerships Alassani, R., ve Göretz, J. (2019). Product placements by micro and macro influencers on Instagram. Social Computing and Social Media. Communication and Social Communities: 11th International Conference, SCSM 2019, Held as Part of the 21st HCI International Conference, (s. 251-267). Springer International Publishing.
  • Anderson, D. (2019). Instagram Follower Magnet Training Guide. Publisher s21598.
  • Anger, I.,ve Kittl, C. (2011). Measuring influence on Twitter. Proceedings of the 11th international conference on knowledge management and knowledge technologies , s. 1-4.
  • Boerman, S. C. (2020). The effects of the standardized Instagram disclosure for micro-and meso-influencers. Computers in human behavior, 103, s. 199-207.
  • Boerman, S. C., Meijers, M. H., ve Zwart, W. (2022). The importance of influencer-message congruence when employing greenfluencers to promote pro-environmental behavior. Environmental Communication, 16(7), s. 920-941.
  • Britt, R. K., Hayes, J. L., Britt, B. C., ve Park, H. (2020). Too big to sell? A computational analysis of network and content characteristics among mega and micro beauty and fashion social media influencers. Journal of Interactive Advertising, 20(2), s. 111-118.
  • Brown, D., ve Hayes, N. (2008). Influencer marketing. Routledge.
  • Bu, Y. P., ve Thaichon, P. (2022). Influencer marketing: sponsorship disclosure and value co-creation behaviour. Marketing Intelligence & Planning, 40(7), s. 854-870.
  • Campbell, C., ve Farrell, J. R. (2020). More than meets the eye: The functional components underlying influencer marketing. Business horizons, 63(4), s. 469-479.
  • Campbell, M. C., ve Kirmani, A. (2000). Consumers' use of persuasion knowledge: The effects of accessibility and cognitive capacity on perceptions of an influence agent. Journal of consumer research, 27(1), s. 69-83.
  • Carman, A. (2024). Paid Impact on Organic.Adjust. Erişim 04.06.2024, https://www.adjust.com/blog/paid-impact-on-organic/
  • Chen, W., Cheng, S., He, X., ve Jiang, F. (2012). Influencerank: An efficient social influence measurement for millions of users in microblog. Second International Conference on Cloud and Green Computing, s. 563-570.
  • Chiu, C. L., ve Ho, H. C. (2023). Impact of celebrity, Micro-Celebrity, and virtual influencers on Chinese gen Z’s purchase intention through social media. SAGE Open, 13(1).
  • Chung, Y. J., Lee, S. S., ve Kim, E. (2023). The effects of influencer types and sponsorship disclosure in instagram sponsored posts. Journal of Current Issues & Research in Advertising, 44(2), s. 193-211.
  • Clark, S. (2023). Metrics Beyond Likes Matter. CMS Wire. Erişim 01.06.2024 https://www.cmswire.com/customer-experience/why-metrics-beyond-likes-matter-in-social-media-strategy/
  • Conde, R., ve Casais, B. (2023). Micro, macro and mega-influencers on instagram: The power of persuasion via the parasocial relationship. Journal of business research.
  • Çetintürk, N. (2019). Temel Dijital Pazarlama Kavramları ve Remarketing Reklam Modeli. Ankara: Seçkin Yayıncılık. Dibble, J. L., Hartmann, T., ve Rosaen, S. F. (2016). Parasocial interaction and parasocial relationship: Conceptual clarification and a critical assessment of measures. Human Communication Research, 42(1), s. 21-44.
  • Doshi, R., Ramesh, A., ve Rao, S. (2022). Modeling Influencer Marketing Campaigns in Social Networks. IEEE Transactions on Computational Social Systems, 10(1), s. 322-334.
  • Duboust, O. (2023). France Has Approved a Law That Targets Influencers. Euronews. Erişim 29.05.2024, https://www.euronews.com/next/2023/06/05/france-has-approved-a-law-that-targets-influencers-what-does-it-mean-for-social-media-star
  • Dumansızoğlu, N. (2023). Müşteriyi anlama yarışı. Capital. Erişim 28.05.2024, https://www.capital.com.tr/yonetim/pazarlama/musteriyi-anlama-yarisi
  • Elwood, A., Gasparin, A., ve Rozza, A. (2021). Ranking micro-influencers: A novel multi-task learning and interpretable framework. 2021 IEEE International Symposium on Multimedia (ISM) , s. 130-137.
  • Evans, D. (2010). Social Media Marketing: The Next Generation of Business Engagement. Wiley.
  • Farivar, S., Wang, F., ve Yuan, Y. (2021). Opinion leadership vs. para-social relationship: Key factors in influencer marketing. Journal of Retailing and Consumer Services, 59.
  • Fenomio. (2023). Erişim 16.09.2023, https://www.fenomio.com
  • Field, A. (2005). Discovering statistics using SPSS for windows: Advanced techniques for beginners. Sage Publications.
  • Friestad, M., ve Wright, P. (1994). The persuasion knowledge model: How people cope with persuasion attempts. Journal of consumer research, 21(1), s. 1-31.
  • Gan, T., Wang, S., Liu, M., Song, X., Yao, Y., ve Nie, L. (2019). Seeking micro-influencers for brand promotion. Proceedings of the 27th ACM International Conference on Multimedia, s. 1933-1941.
  • Gerlich, M. (2022). Micro-influencer marketing during the COVID-19 pandemic: New vistas or the end of an era? Journal of Digital & Social Media Marketing, 9(4), s. 354-370.
  • GetHyped. (2020). Types of Influencers. Erişim 01.06.2024, https://gethypedmedia.com/types-of-influencers/
  • Goward, C. (2012). You Should Test That: Conversion Optimization for More Leads, Sales and Profit or The Art and Science of Optimized Marketing. John Wiley & Sons.
  • Güneş. (2021). Gönderi Başına Yüksek Kazanç. Güneş Gazetesi. Erişim 27.05.2024, https://www.gunes.com/magazin/danla-bilic-duygu-ozaslan-gamze-ercel-aslihan-dogan-turan-gonderi-basina-yuksek-kazanc-1118966
  • Himelboim, I., ve Golan, G. J. (2023). A Social Network Approach to Social Media Influencers on Instagram: The Strength of Being a Nano-Influencer in Cause Communities. Journal of Interactive Advertising, 23(1), s. 1-13.
  • Hirose, A. (2023). Instagram Algorithm. HootSuite. Erişim 01.06.2024, https://blog.hootsuite.com/instagram-algorithm/
  • Hwang, K., ve Zhang, Q. (2018). Influence of parasocial relationship between digital celebrities and their followers on followers’ purchase and electronic word-of-mouth intentions, and persuasion knowledge. Computers in human behavior, 173, s. 155-173.
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Nano, Mikro, Mid-Tier, Makro, Mega: Dijital Pazarlamada Influencer Türü ile İş Birliği Reklamlarının Verimliliği Arasındaki İlişki

Yıl 2024, Sayı: 41, 76 - 103, 29.12.2024

Naim Çetintürk

https://doi.org/10.16878/gsuilet.1420953

Öz

Bu çalışma takipçi sayısına göre influencer’ların çeşitli verimlilik faktörleriyle olan ilişkisini anlamayı amaçlamaktadır. Türkiye’deki 1446 influencer’a ait veriler tanımlayıcı istatistik, çoklu regresyon analizi ve farklılık analizi ile incelenmiştir. Tanımlayıcı istatistikler organik etkileşim açısından en az takipçiye sahip Nano grubunun diğerlerine göre oldukça yüksek bir skora sahip olduğunu ve ücretli reklam gönderilerinde takipçi sayısı arttıkça etkileşim oranının azaldığını göstermektedir. Çoklu regresyon analizi ise influencer türü ve gönderi şekli (ücretli/organik) ile elde edilen etkileşim oranı arasında anlamlı bir ilişki olduğunu ortaya koymaktadır. Etkileşim oranı aynı zamanda erişilen kişi başı maliyet ve etkileşim maliyeti ile ilişkilidir. Geçmiş çalışmalarda değinilmemiş unsurlar olan erişilen kişi başı maliyet (CPP – Cost Per Person) ve satış başı maliyet (CPS - Cost Per Sales) rakamları da etkileşim oranı ile anlamlı bir ilişkiye sahiptir. İki yönlü varyans analizi sonuçları da etkileşim oranlarının gerek influencer türü gerekse gönderi türüne göre güçlü bir şekilde ayrıştığını göstermektedir.

Anahtar Kelimeler

influencer dijital pazarlama reklam e-ticaret sosyal medya

Kaynakça

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  • T.C. Ticaret Bakanlığı. (2021). Sosyal Medya Etkileyicileri Tarafından Yapılan Ticari Reklam ve Haksız Ticari Uygulamalar Hakkında Kılavuz. Erişim 01.06.2024, https://tuketici.ticaret.gov.tr/data/60927f5b13b876f954d58bd1/Sosyal%20Medya%20Etkileyicileri%20Taraf%C4%B1ndan%20Yap%C4%B1lan%20Ticari%20Reklam%20ve%20Haks%C4%B1z%20Ticari%20Uygulamalar%20Hakk%C4%B1nda%20K%C4%B1lavuz.docx
  • Trendyol TMS. (2023). Erişim 01.06.2024, https://tms.trendyol.com/
  • Vora, A. (2023). Organic vs. Paid Marketing. SEMRush. Erişim 03.06.2024, https://www.semrush.com/blog/organic-vs-paid-marketing/
  • Vrontis, D., Makrides, A., Christofi, M., ve Thrassou, A. (2021). Social media influencer marketing: A systematic review, integrative framework and future research agenda. International Journal of Consumer Studies, 45(4), s. 617-644.
  • Wan, S., Koh, R., Ong, A., ve Pang, A. (2015). Parody social media accounts: Influence and impact on organizations during crisis. Public Relations Review, 41(3), s. 381-385.
  • Wang, S., Gan, T., Liu, Y., Zhang, L., Wu, J., ve Nie, L. (2021). Discover Micro-Influencers for Brands via Better Understanding. IEEE Transactions on Multimedia, s. 2595-2605.
  • Wei, M. L., Fischer, E., ve Main, K. J. (2008). An examination of the effects of activating persuasion knowledge on consumer response to brands engaging in covert marketing. Journal of Public Policy & Marketing, 27(1), s. 34-44.
  • Ye, G., Hudders, L., De Jans, S., ve De Veirman, M. (2021). The value of influencer marketing for business: A bibliometric analysis and managerial implications. Journal of Advertising, 50(2), s. 160-178.
  • Yeniçağ. (2019). Az takipçili kullanıcıya daha fazla reklam! Yeniçağ Gazetesi. Erişim 01.06.2024, https://www.yenicaggazetesi.com.tr/az-takipcili-kullaniciya-daha-fazla-reklam-254285h.htm
  • Yuan, C. L., Kim, J., ve Kim, S. J. (2016). Parasocial relationship effects on customer equity in the social media context. Journal of Business Research, 69(9), s. 3795-3803.
  • Yuan, S., ve Lou, C. (2020). How social media influencers foster relationships with followers: The roles of source credibility and fairness in parasocial relationship and product interest. Journal of Interactive Advertising, 20(2), s. 133-147.
  • Zhang, Y., Lin, Y., ve Goh, K. H. (2018). Impact of Online Influencer Endorsement on Product Sales: Quantifying Value of Online Influencer. PACIS.
  • Zwicker, S., Tarabashkina, L., Proksch, M., ve Hardiman, M. (2023). How Micro-Influencers’ Personality Influences the Personality of Novice and Established Brands. Australasian Marketing Journal.
Toplam 82 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular İletişim Teknolojisi ve Dijital Medya Çalışmaları, Sosyal Medya Uygulamaları ve Analizi
Bölüm Makaleler
Yazarlar

Naim Çetintürk 0000-0002-8681-320X

Yayımlanma Tarihi 29 Aralık 2024
Gönderilme Tarihi 16 Ocak 2024
Kabul Tarihi 18 Aralık 2024
Yayımlandığı Sayı Yıl 2024Sayı: 41

Kaynak Göster

APA Çetintürk, N. (2024). Nano, Mikro, Mid-Tier, Makro, Mega: Dijital Pazarlamada Influencer Türü ile İş Birliği Reklamlarının Verimliliği Arasındaki İlişki. Galatasaray Üniversitesi İletişim Dergisi(41), 76-103. https://doi.org/10.16878/gsuilet.1420953
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