Pazarlama Araştırmasında Büyük Veri Analizi ve Kalın Veri Araştırmasının Metodolojik Entegrasyonunun Avantajlarını Keşfetmek: Dijital Çağda Niteliksel Bir Yaklaşım Gereksinimi

Büyük veri alanında devam eden artış, bilgi teknolojisindeki gelişmelerle birleştiğinde, birçok şirketi pazarlama stratejilerini dijital ortama kaydırmaya sevk etmiş ve geleneksel pazarlama yaklaşımlarını giderek geçersiz kılmıştır. Bununla birlikte, mahremiyetle ilgili etik tartışmalara ek olarak, mevcut piyasa koşulları, her zamankinden daha sofistike tüketici içgörülerinin sağlanmasına ilişkin zayıflıklar nedeniyle büyük verilere aşırı güven konusunda şüphe uyandırmıştır. Bu nedenle, pragmatik pazarlama araştırması yaklaşımlarında artık büyük verinin kalın veri ile entegrasyonuna giderek daha fazla önem verilmektedir. Sonuç olarak, bu makale, dijitalleştirilmiş nitel girişimlerin uygulanabilirliği ile, pazarlama araştırmasında karma yöntemleri uygulama girişimlerini gözden geçirerek böyle bir metodolojik entegrasyon gerekliliğini göstermeyi amaçlamaktadır. Son olarak, bu araştırma, pazarlama sürecinde yalnızca tüketici davranışına ilişkin belirli içgörüler elde etmek için değil, aynı zamanda büyük veri çağındaki daha geniş karmaşık pazar eğilimlerini tam olarak kavrama girişimlerinde de kalın verilerin hala gerekli olduğunu tartışacaktır.

Exploring the Advantages of a Methodological Integration of Big Data Analysis and Thick Data Investigation in Marketing Research: The Requirement for a Qualitative Approach in the Digital Era

The continuing increase in big data combined with developments in information technology has prompted many companies to shift marketing strategies into the digital environment, making traditional marketing approaches seem increasingly obsolete. However, in addition to ethical debates regarding privacy, current market conditions have cast doubt on the overreliance of big data due to weaknesses regarding the provision of ever more sophisticated consumer insights. Therefore, emphasis is now increasingly placed on an integration of big data with thick data in pragmatic marketing research approaches. Consequently, this paper aims to illustrate the requirement for such a methodological integration by reviewing attempts to implement mixed methods in marketing research, together with the viability of digitalised qualitative initiatives. Finally, this paper will argue that thick data is still required during the marketing process, not only to gain specific insights into consumer behaviour, but also in attempts to fully comprehend broader complex market trends in the era of big data.

___

  • Ang, Y. Y. (2019). Integrating big data and thick data to transform public services delivery. IBM Center for the Business of Government.
  • BBVA (2020, May 26). The five V’s of big data[Blog Post]. Retrieved from: https://www.bbva.com/en/five-vs-big-data/
  • Bibby, C., Gordon, J., Schüler, G. and Stein, E. (2021, March 25). The big reset: Data-driven marketing in the next normal[Blog Post]. Retrieved from: https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/the-big-reset-data-driven-marketing-in-the-next-normal
  • Blum, K. (2021, August 5). 7 Key shifts in marketing channel spend in 2021[Blog Post]. Retrieved from: https://www.gartner.com/en/marketing/insights/articles/7-key-shifts-in-marketing-channel-spend-in-2021
  • Charm, T., Dhar, R., Haas, S., Liu, J., Novemsky, N. And Teichner, W. (2022, July, 24). Understanding and shaping consumer behavior in the next normal[Blog Post]. Retrieved from: https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/understanding-and-shaping-consumer-behavior-in-the-next-normal
  • Chauhan, A. (2022, October 17). This is how DoorDash uses machine learning & optimization models for delighting their customers[Blog Post]. Retrieved from: https://www.techaheadcorp.com/blog/this-is-how-doordash-uses-machine-learning-optimization-models-for-delighting-their-customers/
  • Collins, B. (2020, October 5). Microsoft in the frame to buy Nokia (again)Forbes[Blog Post]. Retrieved from: https://www.forbes.com/sites/barrycollins/2020/10/05/microsoft-in-the-frame-to-buy-nokia-again/?sh=1af7ffb37228
  • Crawford, K. (2013, April 1). The hidden biases in big data[Blog Post]. Retrieved from: https://hbr.org/2013/04/the-hidden-biases-in-big-data
  • Datareportal (2022, August 15). Twitter statistics and trends[Blog Post]. Retrieved from: https://datareportal.com/essential-twitter-stats
  • Delli Paoli, A. and D’Auria, V. (2021). Digital ethnography: a systematic literature review. Italian Sociological Review, 11(4S), 243–267.
  • Duhigg, C. (2012, February 19). How companies learn your secrets[Blog Post]. Retrieved from: https://www.nytimes.com/2012/02/19/magazine/shopping-habits.html
  • Grebe, M., Rüßmann, M., Franke, M. R. and Anderson, W. (2021, June 21). The leaders’ path to digital value [Blog Post]. Retrieved from: https://www.bcg.com/publications/2021/digital-acceleration-index
  • Harford, T. (2020). The data detective: ten easy rules to make sense of statistics. New York: Riverhead Books.
  • Heinonen, K. and Medberg, G. (2018). Netnography as a tool for understanding customers: Implications for service research and practice. Journal of Services Marketing, 32(6), 657–679.
  • Hunneman, A. (2020, May 20). The do’s and don’ts for marketing in a recession. [Blog Post]. Retrieved from: https://www.bi.edu/research/business-review/articles/2020/05/the-dos-and-donts-for-marketing-in-a-recession/
  • IBM (2022). Cost of a data breach 2022: A million-dollar race to detect and respond. Retrieved from: https://www.ibm.com/reports/data-breach
  • Reinsel, D., Gantz, J. and Rydning, J. (2018, Nowember). The digitization of the world: From edge to core. IDC White Paper.
  • Ives, N. (2019, July 30). JPMorgan Chase taps AI to make marketing messages more powerful. [Blog Post]. Retrieved from: https://www.wsj.com/articles/jpmorgan-chase-taps-ai-to-make-marketing-messages-more-powerful-11564482606
  • Kerin, R. and Hartley, S. (2021). Marketing. New York: McGraw Hill.
  • Kozinets, R. (2015). Netnography: Redefined. New York: SAGE Publications.
  • Leaver, S. (2021, October 15). Predictions 2021: Technology and customer obsession help firms emerge from crisis mode. [Blog Post]. Retrieved from: https://www.forrester.com/blogs/business-trends-2021/
  • Leone, C. (2022, January 14). How much should you budget for marketing in 2022? [Blog Post]. Retrieved from: https://www.webstrategiesinc.com/blog/how-much-budget-for-online-marketing
  • Madsbjerg, C. and Rasmussen, M. B. (2014). An anthropologist walks into a bar. Harvard Business Review, 92(3), 80–90.
  • Mannik, L. and McGarry, K. (2017). Practicing ethnography. Toronto: University of Toronto Press.
  • Market Business News (2015, August 31). What is marketing intelligence? [Blog Post]. Retrieved from: https://marketbusinessnews.com/financial-glossary/market-intelligence/
  • Martin, K. D. and Murphy, P. E. (2017). The role of data privacy in marketing. Journal of the Academy of Marketing Science, 45(135), 135–155.
  • Martin, K. E. (2015). Ethical issues in the big data industry. MIS Quarterly Executive, 14(2), 67–85.
  • Mayer-Schönberger, V. and Cukier, K. (2013). Big data: A revolution that will transform how we live, work, and think. Boston: Houghton Mifflin Harcourt Publishing.
  • McKenna, R. (2021). Persuasion and intellectual autonomy. J. Matheson & K. Lougheed (Ed.). Epistemic Autonomy in (pp.1-20). London: Routledge.
  • McKinsey Company (2020). How COVID-19 has pushed companies over the technology tipping point—and transformed business forever[Blog Post]. Retrieved from: https://www.mckinsey.com/capabilities/strategy-and-corporate-finance/our-insights/how-covid-19-has-pushed-companies-over-the-technology-tipping-point-and-transformed-business-forever
  • Moisander, J., Närvänen, E. and Valtonen, A. (2020). Interpretive marketing research: Using ethnography in strategic market development. L. M. Visconti, L. Peñaloza, & N. Toulouse (Ed.). Marketing management: a cultural perspective in (volume:1) London: Routledge.
  • Pew Research Center (2019, April 24). Sizing up Twitter users [Blog Post]. Retrieved from: https://www.pewresearch.org/internet/2019/04/24/sizing-up-twitter-users/
  • Rasmussen, M. and Hansen, A. W. (2015, November 16). Big data is only half the data marketers need [Blog Post]. Retrieved from: https://hbr.org/2015/11/big-data-is-only-half-the-data-marketers-need
  • Siodmok, A. (2020, January 17). Lab long read: Human-centred policy? blending ‘big data’ and ‘thick data’ in national policy[Blog Post]. Retrieved from: https://openpolicy.blog.gov.uk/2020/01/17/lab-long-read-human-centred-policy-blending-big-data-and-thick-data-in-national-policy/
  • Smaje, K. and Zemmel, R. (2022). Digital transformation on the CEO agenda. McKinsey Digital[Blog Post]. Retrieved from: https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/digital-transformation-on-the-ceo-agenda
  • Spiegelhalter, D. (2019). The art of statistics: How to learn from data. New York: Basic Books.
  • Strong, C. (2015). Humanizing big data: Marketing at the meeting of data, social science and consumer insight. New York: Kogan Page Limites.
  • Thompson, C. J. (2019). The ‘big data’ myth and the pitfalls of ‘thick data’ opportunism: On the need for a different ontology of markets and consumption. Journal of Marketing Management, 35(3-4), 207–230.
  • Valero, P. M. (2017, August 28). How thick data changed Netflix. [Blog Post]. Retrieved from: https://blog.antropologia2-0.com/en/how-thick-data-changed-netflix/
  • Wang, T. (2016, January 20). Why big data needs thick data. Medium. [Blog Post]. Retrieved from: https://medium.com/ethnography-matters/why-big-data-needs-thick-data-b4b3e75e3d7
  • Wang, T. (2017, July 19). The human insights missing from big data [Video]. Retrieved from: https://www.ted.com/talks/tricia_wang_the_human_insights_missing_from_big_data/up-next?language=en
  • Wertenbroch, K. (2021). Marketing automation: Marketing utopia or marketing dystopia? NIM Marketing Intelligence Review, 13(1), 18–23.