User:Gianni mb luce/Big data
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Marketing[edit]
In marketing significance topic is notable because of the constant “datafication”[1] of every day consumers of the internet in witch all forms of data are tracked. The datafication consumers can be defined as quantifying many or all of human behaviors and be used for marketing.[2] because the increasingly more digital world of rapid datafication makes this idea relevant to marketing because the amount of data constantly grows exponentially. It is predicted to increase from 44 to 163 zettabytes within the span of fives years[3]. Because of the size of big data many marketers have with it can often be difficult to navigate[4]. This makes the usefulness to most adapters of big data have a disadvantage. Because of its size its hard time do basic algorithmic findings[5]Big data in marketing is a highly lucrative tool that can be used for big corporations. It is such a valuable asset because of the possibility of predicting significant trends, interests, or statistical outcomes. In a consumer-based manner.[6]
There are three significant factors into the use of big data in marketing.
- Big data provides is customer behavior pattern spotting for marketers since all of human actions are being quantified into readable numbers for marketers to analyze and to use for their research.[7]
- Real-time market responsiveness is huge for marketers because of the ability to shift your marketing efforts and correct to current trends is helpful to staying relevant to your consumers. This can supply corporations with the information necessary to know the consumers' wants and needs before they recognize they need them.[8]
- Data-driven market ambidexterity are being highly fueled by big data[9]. Now new models and algorithms are being made to make significant predictions about certain economic and social situations[10]
References[edit]
- ^ Strong, C. (2015). Humanizing big data : marketing at the meeting of data, social science and consumer insight. Kogan Page.
- ^ Strong, C. (2015). Humanizing big data : marketing at the meeting of data, social science and consumer insight. Kogan Page.
- ^ Berisha, B., Mëziu, E., & Shabani, I. (2022). Big data analytics in Cloud computing: An overview. Journal of Cloud Computing, 11(1), 1-10. https://doi.org/10.1186/s13677-022-00301-w
- ^ Bosch, Volker (2016-11-01). "Big Data in Market Research: Why More Data Does Not Automatically Mean Better Information". NIM Marketing Intelligence Review. 8 (2): 56–63. doi:10.1515/gfkmir-2016-0017.
- ^ McFarland, Daniel A; McFarland, H Richard (2015-12-01). "Big Data and the danger of being precisely inaccurate". Big Data & Society. 2(2): 205395171560249. doi:10.1177/2053951715602495. ISSN 2053-9517.
- ^ Sivarajah, Uthayasankar; Kamal, Muhammad Mustafa; Irani, Zahir; Weerakkody, Vishanth (2017-01-01). "Critical analysis of Big Data challenges and analytical methods". Journal of Business Research. 70: 263–286. doi:10.1016/j.jbusres.2016.08.001. ISSN 0148-2963.
- ^ De Luca, Luigi M.; Herhausen, Dennis; Troilo, Gabriele; Rossi, Andrea (2021-07-01). "How and when do big data investments pay off? The role of marketing affordances and service innovation". Journal of the Academy of Marketing Science. 49 (4): 790–810.
- ^ De Luca, Luigi M.; Herhausen, Dennis; Troilo, Gabriele; Rossi, Andrea (2021-07-01). "How and when do big data investments pay off? The role of marketing affordances and service innovation". Journal of the Academy of Marketing Science. 49 (4): 790–810.
- ^ De Luca, Luigi M.; Herhausen, Dennis; Troilo, Gabriele; Rossi, Andrea (2021-07-01). "How and when do big data investments pay off? The role of marketing affordances and service innovation". Journal of the Academy of Marketing Science. 49 (4): 790–810.
- ^ Grybauskas, Andrius; Pilinkienė, Vaida; Stundžienė, Alina (2021-08-03). "Predictive analytics using Big Data for the real estate market during the COVID-19 pandemic". Journal of Big Data. 8(1): 105. doi:10.1186/s40537-021-00476-0. ISSN 2196-1115. PMC 8329615. PMID 34367876.