EN ÇOK SATAN OTOMOBİL MARKALARININ TWITTER İLETİŞİMLERİNE YÖNELİK BİR ARAŞTIRMA

Sosyal medya siteleri sayesinde markalar mevcut ve potansiyel müşterileriyle sosyal ilişkiler ku­rup yönetebilmektedir. Markalar, sosyal medya kanalıyla, bilinirliklerini artırabilir, ürün ve hizmet­leri hakkında takipçilerine bilgi verebilir ve çeşitli amaçlara sahip kampanyalarını ve kurumsal mesaj­larını duyurabilirler. Bu çalışmada, küresel ölçekte en çok kullanılan sosyal medya sitelerinden olan Twitter üzerinde, markaların sosyal medya kullanımlarının analiz edilmesi amaçlanmaktadır. Bu he­defe ulaşmak için, öncelikle sosyal medya kavramı, karakteristikleri ve kullanım özellikleri incelen­miştir. Sonrasında marka iletişim kavramı ve marka iletişiminde sosyal medya kullanımının önemi incelenmiştir. Türkiye Otomotiv Distribütörleri Derneği’nin 2017 Ocak-Mart Perakende Otomobil Satışları raporuna göre Renault, Hyundai ve Fiat en çok satan otomobil markaları arasında yer almak­tadır. Dolayısıyla bu markaların Twitter hesapları araştırmamıza konu edilmiştir. Belirtilen otomobil markalarının resmi Twitter hesaplarında 1 Aralık 2016 ile 28 Şubat 2017 arasında yaptıkları paylaşım­lara yönelik içerik analizi yapılmıştır. Analiz sonuçlarına göre belirtilen otomobil markalarının, bilgi paylaşma amaçlı iletişim yaptıkları, farklı amaçlar için aynı Twitter hesabını kullandıkları ve takipçile­riyle etkileşim aşamasında onları yeteri kadar onaylamadıkları tespit edilmiştir.

A RESEARCH ON TOP SELLER AUTOMOBILE BRANDS’ COMMUNICATIONS VIA TWITTER

Thanks to social media sites, brands can increase their awareness, let their followers know about their products and services, announce different types of campaigns for various purposes and pitch their corporate messages. As more people join social media sites and use them regularly, social me­dia landscape is bound to get bigger in the future. Social media has grown as a competitor to traditi­onal media and has been an important component of integrated marketing communications. Consu­mers participate in social media sites such as Twitter, Facebook, Instagram, and YouTube, and share their experiences with brands’ products and services on these platforms. Brands can also create online profiles, get featured on social media by introducing these profiles on brand websites, and try to use relational messages to optimize their relationship with their prospective and current customers. The flexible structure of social media allows rapid dissemination of messages. Therefore, social media pro­vide great opportunities to brand managers who want to have a positive effect with positive mouth-to-mouth (WOM) communication. In addition to this, Twitter enables brands to communicate with their existing and potential customers by using an electronic WOM (e-WOM) tool. E-WOM is a new chan­nel for consumers to express their thoughts and it is more effective than traditional WOM due to its access to wider audiences. Most of the text-based information provided to e-WOM are available on the Internet is archived and can thus be used for an indefinite period. Therefore, e-WOM is much more reliable than other sources on the Internet since it is written and archived. Millions of users share their thoughts on different topics related to everyday life through micro-blogging. Micro-blogging is one of the newest forms of social media and is often associated with Twitter. The use of Twitter by brands also revealed the use of Twitter as an internal communication and online listening tool. Furthermore, Twitter might be accepted as a tool to generate e-WOM and go viral. By increasing consumer enga­gement in brand communications and encouraging e-WOM behaviors, brands can make more per­sonalized and targeted marketing communications. Information about the brand’s products, services, and associated links are among the most frequently used content types by the brands on Twitter. The purpose of this paper is to analyze social media usage styles of brands and their brand communica­tions behavior on Twitter. There are several reasons why Twitter was used in this study instead of ot­her social media sites such as Facebook, YouTube, and Instagram. First, Twitter enables users to con­nect and maintain others based on their common interests and activities. Second, Twitter users range from regular users to celebrities, from company representatives to politicians and even to presidents. Therefore, it is possible to get ideas from different interest groups easily in the form of text messages. Renault, Hyundai, and Fiat were among the best-selling car brands in Turkey according to the Janu­ary-March 2017 Retail Automotive Sales report of Automotive Distributors Association Turkey. This is why those brands’ Twitter accounts were chosen. The specified automobile brands’ tweets posted between December 1, 2016, and February 28, 2017 were analyzed with content analysis and they were coded to reflect both interpersonal and machine interaction. First, tweets were classified to reflect in­terpersonal interaction. Tweets indicated as highly interactive if they contain tags, as medium intera­ctive if they contain retweets or referrals, and as low interactive if they contain a response to some­one else. Tweets containing only one level of interactivity were classified as fully interactive. In order to indicate machine interaction, tweets were coded separately, allowing users to choose to access ad­ditional material such as hyperlinks. Afterward, the tweets of all three brands were categorized manu­ally according to the literature. These categories were examined under six major titles: conversational, pass along, news, status, phatic, and spam. Furthermore, it was found that these mentioned automo­bile brands’ tweets showed differences in categories such as conversational, pass along, news, status, phatic, and spam in terms of content. It was also determined that starting social media communicati­ons before the competitors did not always provide an efficient brand communications strategy. Brands should use separate Twitter accounts for different purposes. Many brands use different Twitter ac­counts for handling customer complaints and show these different account addresses in their profiles. However, in this current study, we saw that all three automobile brands had single Twitter accounts for many different purposes. Last but not least, we found that these top seller automobile brands lost the opportunity to reach their followers by communicating with auto industry influencers

___

  • Araujo, T., Neijens, P. & Vliegenthart, R. (2017). Getting the word out on Twitter: The role of influentials, information brokers and strong ties in building word-of-mouth for brands. International Journal of Advertising, 36(3), 496–513. https://doi.org/10.1080/02650.487.2 016.1173765 Asur, S. & Huberman, B. A. (2010). Predicting the future with social media. In 2010 IEEE/WIC/ ACM International Conference on Web Intelligence and Intelligent Agent Technology (pp. 492–499). IEEE. https://doi.org/10.1109/WI-IAT.2010.63 Boyd, D.M. & Ellison, N.B. (2007) Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13, 210-230. Burton, S. & Soboleva, A. (2011). Interactive or reactive? Marketing with Twitter. Journal of Consumer Marketing, 28(7), 491–499. https://doi.org/10.1108/073.637.61111181473 Chatterjee, P. (2001). Online Reviews – Do consumers use them? ACR 2001 Proceedings, 18 (May 2006), 129–134. Chevalier, J. A. & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews. Journal of Marketing Research, 43(3), 345–354. https://doi.org/10.1509/jmkr.43.3.345Crawford, K. (2009, August 27). Following you: Disciplines of listening in social media. Continuum. Taylor & Francis Group. https://doi.org/10.1080/103.043.10903003270 Dann, S. (2010). Twitter content classification. First Monday, 15(12). https://doi.org/10.5210/ fm.v15i12.2745 De Bruyn, A. & Lilien, G. L. (2008). A multi-stage model of word-of-mouth influence through viral marketing. International Journal of Research in Marketing, 25(3), 151–163. https:// doi.org/10.1016/j.ijresmar.2008.03.004 Ehrlich, K. & Shami, N. S. (2010). Microblogging inside and outside the workplace. The Fourth International AAAI Conference on Weblogs and Social Media Microblogging, (May 2014), 42–49. Fong, J.& Burton, S. (2008). A cross-cultural comparison of electronic word-of-mouth and country-of-origin effects. Journal of Business Research, 61(3), 233–242. https://doi. org/10.1016/j.jbusres.2007.06.015 Hoffman, D. L.& Novak, T. P. (1996). Marketing in hypermedia environmen foundations: Conceptual foundations. Journal of Marketing, 60(3), 50–68. https://doi.org/10.2307/1251841 Huberman, B. A., Romero, D. M. & Wu, F. (2008). Social networks that matter: Twitter under the microscope. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.1313405 Hung, K. H. & Li, S. Y. (2007). The influence of eWOM on virtual consumer communities: Social capital, consumer learning, and behavioral outcomes. Journal of Advertising Research, 47(4). https://doi.org/10.2501/S002.184.990707050X Jansen, B. J., Zhang, M., Sobel, K. & Chowdury, A. (2009). Twitter power: Tweets as electronic word of mouth. Journal of the American Society for Information Science and Technology, 60(11), 2169–2188. https://doi.org/10.1002/asi.21149 Karasar, N. (2007). Bilimsel Araştırma Yöntemi: Kavramlar, Ilkeler, Teknikler – Niyazi Karasar – Google Kitaplar (17. basım). Ankara: Nobel Yayın Dağıtım Ltd. Şti. 08.08.2017 tarihinde https://books. google.com.tr/books?id=ZwGhnQEACAAJvedq=niyazi+karasarvehl=trvesa=Xveredir_ esc=y adresinden erişildi. Keller, K. L. (2016). Unlocking the power of integrated marketing communications: How integrated is your IMC program? Journal of Advertising, 45(3), 286–301. https://doi.org/1 0.1080/00913.367.2016.1204967 Killian, G. & McManus, K. (2015). A marketing communications approach for the digital era: Managerial guidelines for social media integration. Business Horizons, 58(5), 539–549. https://doi.org/10.1016/j.bushor.2015.05.006 Kulshrestha, J., Zafar, M. B., Noboa, L. E., Gummadi, K. P. & Ghosh, S. (2015). Characterizing Information Diets of Social Media Users. Association for the Advancement of Artificial Intelligence (Www.aaai.org). https://arxiv.org/pdf/1704.01442.pdf (E.T: 15.08.2017)Kwak, H., Lee, C., Park, H. & Moon, S. (2010). What is Twitter, a Social Network or a News Media? https://an.kaist.ac.kr/~haewoon/papers/2010-www-Twitter.pdf (E.T: 01.08.2017) Kwon, E. S., Kim, E., Sung, Y. & Yoo, C.Y. (2014). Brand followers. International Journal of Advertising, 33(4), 657–680. https://doi.org/10.2501/IJA-33-4-657-680 Li, F. & Du, T. C. (2011). Who is talking? An ontology-based opinion leader identification framework for word-of-mouth marketing in online social blogs. Decision Support Systems, 51(1), 190–197. https://doi.org/10.1016/j.dss.2010.12.007 Lin, J.-S. & Peña, J. (2011). Are you following me? A content analysis of tv networks’ brand communication on Twitter. Journal of Interactive Advertising, 12(1), 17–29. https://doi.or g/10.1080/15252.019.2011.10722188 Medya, S. (2017). no:1 4-10. Impact, 1. http://www.skalamedya.com.tr/assets/image/uploads/ pdf/otomotiv.pdf (E.T: 01.09.2017) Miller, V. (2018). New media, networking and phatic culture. Convergence: The Interantional Journal of Research into New Media Technologies, 14(4), 387-400. Otomotiv Distribütörleri Derneği. (2018). Pazar – Perakende Satışlar. http://www.odd.org.tr/ web_2837_1/neuralnetwork.aspx?type=36 (E.T:27.05.2018) Pak, A. & Paroubek, P. (2010). Twitter as a Corpus for Sentiment Analysis and Opinion Mining. In Proceedings of the Seventh Conference on International Language Resources and Evaluation, 1320–1326. https://doi.org/10.1371/journal.pone.0026624 Rafaeli, S. & Sudweeks, F. (1997). Networked interactivity. Journal of Computer-Mediated Communication, 2(4), JCMC243 https://doi.org/10.1111/j.1083-6101.1997.tb00201.x Sundar, S. S., Kalyanaraman, S.& Brown, J. (2003). Explicating Web Site Interactivity: Impression Formation Effects in Political Campaign Sites. Communication Research, 30(1), 30–59. https://doi.org/10.1177/009.365.0202239025 Tischler, M. E., Friedrichs, D., Coll, K. & Williamson, J. R. (1977). Pyridine nucleotide distributions and enzyme mass action ratios in hepatocytes from fed and starved rats. Archives of Biochemistry and Biophysics, 184(1), 222–236. https://doi.org/10.1016/0003- 9861(77)90346-0
Öneri Dergisi-Cover
  • ISSN: 1300-0845
  • Yayın Aralığı: Yılda 2 Sayı
  • Başlangıç: 1994
  • Yayıncı: Marmara Üniversitesi