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Büyük Verinin Pazarlama Karması Üzerindeki Etkileri

Yıl 2022, , 969 - 980, 26.09.2022
https://doi.org/10.32709/akusosbil.896934

Öz

Bu çalışmada, büyük veri kavramının pazarlama karması üzerindeki etkileri incelenmiştir. İlk olarak, pazarlama karması açıklanıp, pazarlama karmasının 4P’si sunulmuştur. Pazarlama karmasının her bir elemanını yani ürün (product), fiyat (price), dağıtım (place) ve tutundurma (promotion) kavramları ayrı ayrı açıklanmıştır. Daha sonra, büyük veri ve büyük veri analizinin özelliklerinden kısaca bahsedilmiştir.. Büyük verinin pazarlama karması bileşenleri üzerindeki etkileri ayrı ayrı incelenmiştir. Son olarak, yapılan bu incelemelerin sonuçları bir başlık altında toplanmıştır. Yapılan araştırmaların sonucunda büyük veri analizinin pazarlama karmasının elemanlarının ele alınış biçimlerinde çeşitli değişiklikler oluşturduğu görülmüştür. Büyük veri analizi ve büyük veri sayesinde amaçlara daha uygun stratejilerin belirlenmesinin daha kolaylaştığı incelenen çalışmalardan tespit edilmiştir.

Kaynakça

  • American Marketing Association. Definition of marketing https://www.ama.org/the-definition-of-marketing-what-is-marketing/ (Erişim tarihi: 25.02.2021)
  • Armstrong, D. (2015). The rise of the marketer. Driving engagement, experience and revenue. A Report from The Economist Intelligence Unit.
  • Atzori, L., Iera, A., Morabito, G. (2010). The internet of things: A survey. Computer Networks, 54(15), 2787-2805.
  • Bil, E., & Özkaya, M. (2021). Dijital pazarlama ve geleneksel pazarlamanın kısa bir karşılaştırılması, Troyacademy, 6(2), 462-476.
  • Borden, N. H. (1965). The concept of the marketing mix. In Schwartz, G. (Ed), Science in marketing. New York: John Wiley & Sons, 386-397.
  • Bradlow, E.T., Gangwar, M., Kopalle, P., Voleti, S. (2017). The role of big data and predictive analytics in retailing. Journal of Retailing, 93 (1), 79-95.
  • Chong, A. Y. L., Ch’ng, E. , Liu ,M. J., Li, B. (2017). Predicting consumer product demands via Big Data: the roles of online promotional marketing and online reviews. International Journal of Production Research, 55,17, 5142-5156.
  • Chui, M., Löffler, M., Roberts, R. (2010). The internet of things. McKinsey Quarterly, 2, 1-9.
  • Cui, W. (2021). Application of big data in the promotion of fast selling products. E3S Web of Conferences 235, 03078.
  • Demirkan, H. & Delen,D. (2013). Leveraging the capabilities of service oriented decision support systems: putting analytics and big data in cloud. Decis.Support Syst. 55(1),412–421.
  • Doyle, P. (1994). Marketing Management and Strategy. Prentice Hall.
  • Drayer, J.& Rascher, D. (2013). Guest Editors’ Introduction: Sport pricing research: Past, persent and future. Sport Marketing Quarterly, 22, 123-128.
  • Erevelles, S., Fukawa, N., Swayne, L. (2016). Big data consumer analytics and the transformation of marketing. Journal of Business Research, 69(2), 897–904.
  • Fan, S., Lau, R.Y.K., Zhao, J.L. (2015). Demystifying big data analytics for business intelligence through the lens of marketing mix. Big Data Research, 2, 28-32.
  • Flowers, S., Mateos-Garcia, J., Sapsed, J., Nightingale, P., Grantham, A., Voss, G. (2008). The New Inventors: How users are changing the rules of innovation. NESTA
  • Goi, C.L. (2011). Perception of Consumer on Marketing Mix: Male vs. Female. 2010 International Conference on Business and Economics Research, 1, IACSIT Press, Kuala Lumpur, Malaysia.
  • Goldsmith R. E. (1999). The Personalised Marketplace: Beyond the 4Ps. Marketing Intelligence and Planning, 17 (4), 178-185.
  • Gunasekaran, A., Papadopoulos, T., Rameswar, D., Wamba, S.R., Childe, S. J., Hazen, B., Akter, S. (2017). Big data and predictive analytics for supply chain and organizational performance. Journal of Business Research, 70, 308-317.
  • Hewage, T. N., Halgamuge, M. N., Syed, A., Ekici, G. (2018). Review: Big data techniques of Google, Amazon, Facebook and Twitter. Journal of Communication, 13, 2, 94-100.
  • IBM. (2015). The impact of the Internet of Things on product development. IBM Corp.
  • Isoraite, M. (2015). Marketing mix theoretical aspects. International Journal of Research-Granthaalayah. 4, 6, 25-37.
  • iCulture. (2016). Dossier: iBeacons.:http://www.iculture.nl/dossiers/ibeacons/ (Erişim tarihi: 25.02.2021)
  • Jeble, S., Kumari, S., Patil, Y. (2018). Role of big data in decision making. Operations and Supply Chain Management, 11, (1), 36-44.
  • Kanth, H., Data mining for marketing, https://www.grin.com/document/293496 (Erişim tarihi: 25.02.2021)
  • Klopper, D.S. (2016). The possibilities and challenges of the application and integration of the Internet of Things for future marketing practice. 7th IBA Bachelor Thesis Conference, July 1st, Enschede, The Netherlands.
  • Kotler, P. (1984). Marketing Management: Analysis, Planning and Control (5th ed.). New Jersey: Prentice-Hall.
  • Lawrence, E., Corbitt, B, Fisher, J.A, Lawrence, J., Tidwell, A. (2000). Internet Commerce (2nd ed.). John Wiley & Sons Australia Ltd, 79.
  • Lowrey, A. (2010). How Much Is That Doggie in the Browser Window?. http://www.slate.com/articles/business/moneybox/2010/12/how_much_is_that_doggie_in_the_browser_window.html (Erişim tarihi: 25.02.2021)
  • Lycett, M. (2013), "Datafication": Making sense of (big) data in complex World. European Journal of Information Systems, 22(3), 381–386.
  • Manyika, J. (2015). The internet of things: mapping the value beyond the hype.
  • Mckinsey&Company. (2015). Marketing & Sales Big data, analytics, and the future of marketing and sales.
  • Mikalef, P., Boura, M. Lekakos, G., Krogstie, J. (2020). The role of information governance in big data analytics driven innovation. Information and Management, 57, 103361.
  • Mohsin, M. (2020) 10 Social media statistics you need to know in 2021(inforgraphic) https://www.oberlo.com/blog/social-media-marketing-statistics. (Erişim tarihi: 25.02.2021)
  • Muala, A.A. & Qurneh, M.A. (2012). Assessing the relationshipbetween marketing mix and loyality through tourist satisfaction in Jordan curative tourism. American Academic & Scholarly Research Journal, 4, 2.
  • Paul, K. (2020). They know us better than we know ourselves’: how Amazon tracked my last two years of reading. https://www.theguardian.com/technology/2020/feb/03/amazon-kindle-data-reading-tracking-privacy. (Erişim tarihi: 25.02.2021).
  • Porter, M. E., & Heppelmann, J. E. (2014). How smart, connected products are transforming competition. Harvard Business Review, 92(11), 64-88.
  • Rafiq, M. & Ahmed, P. K. (1995). Using the 7Ps as a Generic Marketing Mix: an Exploratory Survey of UK and European Marketing Academics, Marketing Intelligence & Planning, 13, 9, 4-15.
  • Riaz, W., Tanveer, A. (n.d). Marketing Mix, Not Branding, Asian Journal of Business and Management Sciences, 1, (11), 43-52.
  • Srinivasan, S., Pauwels, K., Hanssens, D.M., Dekimpe, M.G. (2004). Do promotions benefit manufacturers, retailers, or both?. Manag. Sci. 50(5), 617–629.
  • Tariq Khan, M. (2014). The concept of marketing mix and its elements. International Journal of Information, Business and Management, 6, 2.
  • Walmart. (2017). 5 ways Walmart uses big data to help costumers, https://corporate.walmart.com/newsroom/innovation/20170807/5-ways-walmart-uses-big-data-to-help-customers. (Erişim tarihi: 25.02.2021).
  • Wang, G., Gunasekaran, A., Ngai, E. W.T., Papadoupoulos, T. (2016). Big data analytics in logistics and supply chain management: Certain inverstigations for research and applications. Int. J. Production Economics, 176, 98-110.
  • WeatherUnlocked, The complete guide to weather based marketing http://www.weatherunlocked.com/resources/the-complete-guide-to-weather-based-marketing/weather-based-marketing-strategies. (Erişim tarihi: 25.02.2021).
  • Xu, Z. (2016). Three essays on big data analytics, traditional marketing analytics, knowledge discovery, and new product performance. Open Access Theses and Dissertations, 781.
  • Zhang, J. & Li, Y. (2017). A simple analysis of revolution and innovation of marketing mix theory from big data perspective. IEEE 2nd International Conference on Big Data Analysis.
  • Zhong, R. Y., Newman, S. T., Huang, G. Q., Lan, Sh. (2016). Big data for supply chain management in the service and manufacturing sectors: Challenges, opportunities, and future perspective. Computer & Industrial Engineering, 101, 572-591.

The Effects of the Big Data Concept on the Marketing Mix

Yıl 2022, , 969 - 980, 26.09.2022
https://doi.org/10.32709/akusosbil.896934

Öz

In this study, the effect of the big data concept on the marketing mix is investigated. Firstly, the marketing mix and present the 4P of the marketing mix are explained. Then, the each element of the marketing mix, such as price, product, place and promotion, are described. Later, the big data and big data analytics are briefly mentioned. Then, the effects of the big data concept on the each element of the marketing mix are analyzed separately. Finally, the results are summarized. As a result of the researches, it has been seen that big data analysis has created various changes in the way the elements of the marketing mix are handled. It has been determined from the studies examined that it has become easier to determine strategies that are more suitable for the purposes by the big data analysis and big data.

Kaynakça

  • American Marketing Association. Definition of marketing https://www.ama.org/the-definition-of-marketing-what-is-marketing/ (Erişim tarihi: 25.02.2021)
  • Armstrong, D. (2015). The rise of the marketer. Driving engagement, experience and revenue. A Report from The Economist Intelligence Unit.
  • Atzori, L., Iera, A., Morabito, G. (2010). The internet of things: A survey. Computer Networks, 54(15), 2787-2805.
  • Bil, E., & Özkaya, M. (2021). Dijital pazarlama ve geleneksel pazarlamanın kısa bir karşılaştırılması, Troyacademy, 6(2), 462-476.
  • Borden, N. H. (1965). The concept of the marketing mix. In Schwartz, G. (Ed), Science in marketing. New York: John Wiley & Sons, 386-397.
  • Bradlow, E.T., Gangwar, M., Kopalle, P., Voleti, S. (2017). The role of big data and predictive analytics in retailing. Journal of Retailing, 93 (1), 79-95.
  • Chong, A. Y. L., Ch’ng, E. , Liu ,M. J., Li, B. (2017). Predicting consumer product demands via Big Data: the roles of online promotional marketing and online reviews. International Journal of Production Research, 55,17, 5142-5156.
  • Chui, M., Löffler, M., Roberts, R. (2010). The internet of things. McKinsey Quarterly, 2, 1-9.
  • Cui, W. (2021). Application of big data in the promotion of fast selling products. E3S Web of Conferences 235, 03078.
  • Demirkan, H. & Delen,D. (2013). Leveraging the capabilities of service oriented decision support systems: putting analytics and big data in cloud. Decis.Support Syst. 55(1),412–421.
  • Doyle, P. (1994). Marketing Management and Strategy. Prentice Hall.
  • Drayer, J.& Rascher, D. (2013). Guest Editors’ Introduction: Sport pricing research: Past, persent and future. Sport Marketing Quarterly, 22, 123-128.
  • Erevelles, S., Fukawa, N., Swayne, L. (2016). Big data consumer analytics and the transformation of marketing. Journal of Business Research, 69(2), 897–904.
  • Fan, S., Lau, R.Y.K., Zhao, J.L. (2015). Demystifying big data analytics for business intelligence through the lens of marketing mix. Big Data Research, 2, 28-32.
  • Flowers, S., Mateos-Garcia, J., Sapsed, J., Nightingale, P., Grantham, A., Voss, G. (2008). The New Inventors: How users are changing the rules of innovation. NESTA
  • Goi, C.L. (2011). Perception of Consumer on Marketing Mix: Male vs. Female. 2010 International Conference on Business and Economics Research, 1, IACSIT Press, Kuala Lumpur, Malaysia.
  • Goldsmith R. E. (1999). The Personalised Marketplace: Beyond the 4Ps. Marketing Intelligence and Planning, 17 (4), 178-185.
  • Gunasekaran, A., Papadopoulos, T., Rameswar, D., Wamba, S.R., Childe, S. J., Hazen, B., Akter, S. (2017). Big data and predictive analytics for supply chain and organizational performance. Journal of Business Research, 70, 308-317.
  • Hewage, T. N., Halgamuge, M. N., Syed, A., Ekici, G. (2018). Review: Big data techniques of Google, Amazon, Facebook and Twitter. Journal of Communication, 13, 2, 94-100.
  • IBM. (2015). The impact of the Internet of Things on product development. IBM Corp.
  • Isoraite, M. (2015). Marketing mix theoretical aspects. International Journal of Research-Granthaalayah. 4, 6, 25-37.
  • iCulture. (2016). Dossier: iBeacons.:http://www.iculture.nl/dossiers/ibeacons/ (Erişim tarihi: 25.02.2021)
  • Jeble, S., Kumari, S., Patil, Y. (2018). Role of big data in decision making. Operations and Supply Chain Management, 11, (1), 36-44.
  • Kanth, H., Data mining for marketing, https://www.grin.com/document/293496 (Erişim tarihi: 25.02.2021)
  • Klopper, D.S. (2016). The possibilities and challenges of the application and integration of the Internet of Things for future marketing practice. 7th IBA Bachelor Thesis Conference, July 1st, Enschede, The Netherlands.
  • Kotler, P. (1984). Marketing Management: Analysis, Planning and Control (5th ed.). New Jersey: Prentice-Hall.
  • Lawrence, E., Corbitt, B, Fisher, J.A, Lawrence, J., Tidwell, A. (2000). Internet Commerce (2nd ed.). John Wiley & Sons Australia Ltd, 79.
  • Lowrey, A. (2010). How Much Is That Doggie in the Browser Window?. http://www.slate.com/articles/business/moneybox/2010/12/how_much_is_that_doggie_in_the_browser_window.html (Erişim tarihi: 25.02.2021)
  • Lycett, M. (2013), "Datafication": Making sense of (big) data in complex World. European Journal of Information Systems, 22(3), 381–386.
  • Manyika, J. (2015). The internet of things: mapping the value beyond the hype.
  • Mckinsey&Company. (2015). Marketing & Sales Big data, analytics, and the future of marketing and sales.
  • Mikalef, P., Boura, M. Lekakos, G., Krogstie, J. (2020). The role of information governance in big data analytics driven innovation. Information and Management, 57, 103361.
  • Mohsin, M. (2020) 10 Social media statistics you need to know in 2021(inforgraphic) https://www.oberlo.com/blog/social-media-marketing-statistics. (Erişim tarihi: 25.02.2021)
  • Muala, A.A. & Qurneh, M.A. (2012). Assessing the relationshipbetween marketing mix and loyality through tourist satisfaction in Jordan curative tourism. American Academic & Scholarly Research Journal, 4, 2.
  • Paul, K. (2020). They know us better than we know ourselves’: how Amazon tracked my last two years of reading. https://www.theguardian.com/technology/2020/feb/03/amazon-kindle-data-reading-tracking-privacy. (Erişim tarihi: 25.02.2021).
  • Porter, M. E., & Heppelmann, J. E. (2014). How smart, connected products are transforming competition. Harvard Business Review, 92(11), 64-88.
  • Rafiq, M. & Ahmed, P. K. (1995). Using the 7Ps as a Generic Marketing Mix: an Exploratory Survey of UK and European Marketing Academics, Marketing Intelligence & Planning, 13, 9, 4-15.
  • Riaz, W., Tanveer, A. (n.d). Marketing Mix, Not Branding, Asian Journal of Business and Management Sciences, 1, (11), 43-52.
  • Srinivasan, S., Pauwels, K., Hanssens, D.M., Dekimpe, M.G. (2004). Do promotions benefit manufacturers, retailers, or both?. Manag. Sci. 50(5), 617–629.
  • Tariq Khan, M. (2014). The concept of marketing mix and its elements. International Journal of Information, Business and Management, 6, 2.
  • Walmart. (2017). 5 ways Walmart uses big data to help costumers, https://corporate.walmart.com/newsroom/innovation/20170807/5-ways-walmart-uses-big-data-to-help-customers. (Erişim tarihi: 25.02.2021).
  • Wang, G., Gunasekaran, A., Ngai, E. W.T., Papadoupoulos, T. (2016). Big data analytics in logistics and supply chain management: Certain inverstigations for research and applications. Int. J. Production Economics, 176, 98-110.
  • WeatherUnlocked, The complete guide to weather based marketing http://www.weatherunlocked.com/resources/the-complete-guide-to-weather-based-marketing/weather-based-marketing-strategies. (Erişim tarihi: 25.02.2021).
  • Xu, Z. (2016). Three essays on big data analytics, traditional marketing analytics, knowledge discovery, and new product performance. Open Access Theses and Dissertations, 781.
  • Zhang, J. & Li, Y. (2017). A simple analysis of revolution and innovation of marketing mix theory from big data perspective. IEEE 2nd International Conference on Big Data Analysis.
  • Zhong, R. Y., Newman, S. T., Huang, G. Q., Lan, Sh. (2016). Big data for supply chain management in the service and manufacturing sectors: Challenges, opportunities, and future perspective. Computer & Industrial Engineering, 101, 572-591.
Toplam 46 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm İktisadi ve İdari Bilimler
Yazarlar

Erkan Bil 0000-0003-4301-3816

Murat Özkaya 0000-0001-7241-4710

Yayımlanma Tarihi 26 Eylül 2022
Gönderilme Tarihi 15 Mart 2021
Yayımlandığı Sayı Yıl 2022

Kaynak Göster

APA Bil, E., & Özkaya, M. (2022). Büyük Verinin Pazarlama Karması Üzerindeki Etkileri. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 24(3), 969-980. https://doi.org/10.32709/akusosbil.896934