Year 2024,
Volume: 8 Issue: 4, 76 - 84, 31.12.2024
Hatice Dilaver
,
Kamil Fatih Dilaver
References
- [1] R.V. Kozinets, & U. Gretzel, (2021).“Commentary: artificial intelligence: the marketer’s dilemma”, Journal of Marketing, Vol. 85 No. 1, pp. 156-159 https://doi.org/10.1177/0022242920972933
- [2] N. Seaver, (2019). Knowing algorithms. DigitalSTS, 412-422.
- [3] I. Lobel, (2021). Revenue management and the rise of the lgorithmic economy. Management Science, 67(9), 1-10
- [4] L. Manovich, (2018). Digital traces in context| 100 billion data rows per second: Media analytics in the early 21st century. International journal of communication, 12, 16.
- [5] O. Şahin, (2021). “Yapay zekâ ve makine öğreniminin pazarlama süreçleri üzerindeki etkileri”, İşletmeciliği Yeniden Düşünmek, içinde (241-258), Türkmen Kitabevi
- [6] T. S. Kumar, (2020). Data mining-based marketing decision support system using hybrid machine learning algorithm. Journal of Artificial Intelligence, 2(03), 185-193.
- [7] P. Gentsch, (2018). AI in marketing, sales and service: How marketers without a data science degree can use AI, big data and bots. Springer.
- [8] P. Roetzer, & M. Kaput, (2022). Marketing Artificial Intelligence: AI, Marketing, and the Future of Business. BenBella Books.
- [9] S. Akter, Y. K., Dwivedi, S. Sajib, K. Biswas, R. J. Bandara, & K. Michael, (2022). Algorithmic bias in machine learning-based marketing models. Journal of Business Research, 144, 201-216.
- [10] M. Z. Shahid, & G. Li, (2019). Impact of artificial intelligence in marketing: a perspective of marketing professionals of pakistan. Global Journal of Management and Business Research: E Marketing, 19(2), 26-33.
- [11] A. Ng, (2016). What artificial intelligence can and can’t do right now. Harvard Business Review, 9.
- [12] S. Hu, (2019). Information Design with Big Data. Cornell University. 161.
- [13] P.K. Kopalle, M. Gangwar, A. Kaplan, D. Ramachandran, W. Reinartz, & A. Rindfleisch (2022). Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities, International Journal of Research in Marketing 39 (2022) 522–540.
- [14] J. Howard, (2019). Artificial intelligence: Implications for the future of work. American Journal of Industrial Medicine, 62(11), 917–926. https://doi.org/10.1002/ajim.23037
- [15] L. Vanneschi, D. M. Horn, M. Castelli, & A. Popovič, (2018). An artificial intelligence system for predicting customer default in e-commerce. Expert Systems with Applications, 104, 1–21. https://marketinginsidergroup.com/content-marketing/marketing-needs-data-driven/ https://doi.org/10.1016/j.eswa.2018.03.025
- [16] H. M. Álvarez, (2015). Marketing Algoritmico Y Marketing Heuristico, Una Cotroversia. Investigación e Innovación en Ingenierías, 3(1).
- [17] T. H. Corman, C. E. Leiserson, R. L. Rivest, & C. Stein, (2022). Introduction to algorithms. MIT press.
- [18] I. Katsov, (2017). Introduction to algorithmic marketing: Artificial intelligence for marketing operations. Ilia Katcov
- [19] E. Bilgiç, & M. F. Esen, (2018). Endüstri 4.0 ışığında veri madenciliği ve pazarlama: son gelişmeler, yeni trendler. İşletme Ekonomi ve Yönetim Araştırmaları Dergisi, 1(2), 21-29.
- [20] R. Venkatesan, & J. Lecinski, (2021). The AI Marketing Canvas: A Five-Stage Road Map to Implementing Artificial Intelligence in Marketing. Stanford University Press.
- [21] S. Akter, Y. K. Dwivedi, S. Sajib, K. Biswas, R. J. Bandara, & K. Michael, (2022). Algorithmic bias in machine learning-based marketing models. Journal of Business Research, 144, 201-216.
- [22] A. Deterred, (2019). “Algorithmic Marketing as a replacement for traditional Marketing Research”, Metropolia University of Applied Sciences Bachelor of Business Administration European Business
Administration Bachelor’s Thesis.
- [23] P. Gentsch, (2018). AI in marketing, sales and service: How marketers without a data science degree can use AI, big data and bots. Springer.
- [24] Y. Heisler, "How Tesla Uses AI to Create Autopilot." Industry Week
- [25] McKinsey & Company. "How AI is transforming the retail experience." McKinsey Report
- [26] N. Hariri, "How Netflix Uses AI to Understand and Delight Its Users." Forbes.
Year 2024,
Volume: 8 Issue: 4, 76 - 84, 31.12.2024
Hatice Dilaver
,
Kamil Fatih Dilaver
Abstract
Algorithmic marketing and big data analysis are among the increasingly important topics in today's business world. With the rapid advancement of technology, businesses need to leverage these new tools to stay competitive and provide better services to their customers. We will discuss the fundamental principles, application areas, and opportunities that algorithmic marketing and big data analysis offer to businesses. Additionally, we will also delve into the challenges that may be encountered and the points that need to be considered in the use of these technologies. Our goal is to provide readers with an understanding of the potential of algorithmic marketing and big data analysis and demonstrate how these technologies can transform business strategies. We hope this book will help businesses capitalize on these new opportunities and gain a competitive advantage.This article aims to provide a comprehensive overview of algorithmic marketing and big data analysis. In today's digital age, it has become inevitable for businesses to make data-driven decisions and base their marketing strategies on this data in order to succeed. The first section of the article offers a general overview of the fundamental principles of algorithmic marketing and how it works. It then delves into a detailed examination of why big data analysis is important for businesses and how it is implemented.The second section of the article addresses the application areas of algorithmic marketing and the differences between sectors. It extensively explores how algorithmic marketing can be utilized in various fields, from digital advertising to e-commerce and social media marketing. In the final section, the article discusses the opportunities and challenges that algorithmic marketing and big data analysis present to businesses. It also speculates on how these technologies could shape the future of the business world and influence business strategies.Readers of the article will develop a deep understanding of algorithmic marketing and big data analysis and learn how to integrate these new technologies into their business strategies.
References
- [1] R.V. Kozinets, & U. Gretzel, (2021).“Commentary: artificial intelligence: the marketer’s dilemma”, Journal of Marketing, Vol. 85 No. 1, pp. 156-159 https://doi.org/10.1177/0022242920972933
- [2] N. Seaver, (2019). Knowing algorithms. DigitalSTS, 412-422.
- [3] I. Lobel, (2021). Revenue management and the rise of the lgorithmic economy. Management Science, 67(9), 1-10
- [4] L. Manovich, (2018). Digital traces in context| 100 billion data rows per second: Media analytics in the early 21st century. International journal of communication, 12, 16.
- [5] O. Şahin, (2021). “Yapay zekâ ve makine öğreniminin pazarlama süreçleri üzerindeki etkileri”, İşletmeciliği Yeniden Düşünmek, içinde (241-258), Türkmen Kitabevi
- [6] T. S. Kumar, (2020). Data mining-based marketing decision support system using hybrid machine learning algorithm. Journal of Artificial Intelligence, 2(03), 185-193.
- [7] P. Gentsch, (2018). AI in marketing, sales and service: How marketers without a data science degree can use AI, big data and bots. Springer.
- [8] P. Roetzer, & M. Kaput, (2022). Marketing Artificial Intelligence: AI, Marketing, and the Future of Business. BenBella Books.
- [9] S. Akter, Y. K., Dwivedi, S. Sajib, K. Biswas, R. J. Bandara, & K. Michael, (2022). Algorithmic bias in machine learning-based marketing models. Journal of Business Research, 144, 201-216.
- [10] M. Z. Shahid, & G. Li, (2019). Impact of artificial intelligence in marketing: a perspective of marketing professionals of pakistan. Global Journal of Management and Business Research: E Marketing, 19(2), 26-33.
- [11] A. Ng, (2016). What artificial intelligence can and can’t do right now. Harvard Business Review, 9.
- [12] S. Hu, (2019). Information Design with Big Data. Cornell University. 161.
- [13] P.K. Kopalle, M. Gangwar, A. Kaplan, D. Ramachandran, W. Reinartz, & A. Rindfleisch (2022). Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities, International Journal of Research in Marketing 39 (2022) 522–540.
- [14] J. Howard, (2019). Artificial intelligence: Implications for the future of work. American Journal of Industrial Medicine, 62(11), 917–926. https://doi.org/10.1002/ajim.23037
- [15] L. Vanneschi, D. M. Horn, M. Castelli, & A. Popovič, (2018). An artificial intelligence system for predicting customer default in e-commerce. Expert Systems with Applications, 104, 1–21. https://marketinginsidergroup.com/content-marketing/marketing-needs-data-driven/ https://doi.org/10.1016/j.eswa.2018.03.025
- [16] H. M. Álvarez, (2015). Marketing Algoritmico Y Marketing Heuristico, Una Cotroversia. Investigación e Innovación en Ingenierías, 3(1).
- [17] T. H. Corman, C. E. Leiserson, R. L. Rivest, & C. Stein, (2022). Introduction to algorithms. MIT press.
- [18] I. Katsov, (2017). Introduction to algorithmic marketing: Artificial intelligence for marketing operations. Ilia Katcov
- [19] E. Bilgiç, & M. F. Esen, (2018). Endüstri 4.0 ışığında veri madenciliği ve pazarlama: son gelişmeler, yeni trendler. İşletme Ekonomi ve Yönetim Araştırmaları Dergisi, 1(2), 21-29.
- [20] R. Venkatesan, & J. Lecinski, (2021). The AI Marketing Canvas: A Five-Stage Road Map to Implementing Artificial Intelligence in Marketing. Stanford University Press.
- [21] S. Akter, Y. K. Dwivedi, S. Sajib, K. Biswas, R. J. Bandara, & K. Michael, (2022). Algorithmic bias in machine learning-based marketing models. Journal of Business Research, 144, 201-216.
- [22] A. Deterred, (2019). “Algorithmic Marketing as a replacement for traditional Marketing Research”, Metropolia University of Applied Sciences Bachelor of Business Administration European Business
Administration Bachelor’s Thesis.
- [23] P. Gentsch, (2018). AI in marketing, sales and service: How marketers without a data science degree can use AI, big data and bots. Springer.
- [24] Y. Heisler, "How Tesla Uses AI to Create Autopilot." Industry Week
- [25] McKinsey & Company. "How AI is transforming the retail experience." McKinsey Report
- [26] N. Hariri, "How Netflix Uses AI to Understand and Delight Its Users." Forbes.