پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 161 |
| تعداد شمارهها | 6,470 |
| تعداد مقالات | 69,914 |
| تعداد مشاهده مقاله | 122,492,596 |
| تعداد دریافت فایل اصل مقاله | 95,720,879 |
Evaluation of the effectiveness of implementing artificial intelligence in the Google Advertising service | ||
| Journal of Information Technology Management | ||
| دوره 16، شماره 4، 2024، صفحه 79-99 اصل مقاله (1.72 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/jitm.2024.99052 | ||
| نویسندگان | ||
| Оlena Chukurn* 1؛ Tetiana Tardaskina2؛ Yuliia Tereshko3؛ Evgene Kholostenko4؛ Viktoria Kofman4؛ Leonid Pankovets5 | ||
| 1Professor, Department of Management and Marketing, State University of Intelligent Technologies and Telecommunications – Kuznechna Street, 1, Odesa, Odesa region, 65000, Ukraine. | ||
| 2Аssociate professor, Department of Management and Marketing, State University of Intelligent Technologies and Telecommunications – Kuznechna Street, 1, Odesa, Odesa region, 65000, Ukraine. | ||
| 3Associate Professor of the Department of Digital Technologies and Design- Analytical Solutions, Technical University Metinvest Polytechnic LLC – Pivdenne highway, 80, Zaporizhzhya, Zaporizhzhya region, 69008, Ukraine. | ||
| 4Department of Management and Marketing, State University of Intelligent Technologies and Telecommunications – Kuznechna Street, 1, Odesa, Odesa region, 65000, Ukraine. | ||
| 5Master of Management, postgraduate student of the third level of higher education, majoring in «Economics», State University of Intelligent Technologies and – Kuznechna street, 1, Odesa, Odesa region, 65000, Ukraine. | ||
| چکیده | ||
| This paper examines the effectiveness of implementing artificial intelligence (AI) in the Google Ads advertising service. The study analyzes the advantages and disadvantages of AI integration, focusing on attribution models and end-to-end analytics. The findings show that traditional metrics, such as CTR, CPC, and ROI, used to evaluate advertising campaign performance, exhibit significant statistical errors when AI tools are applied, with errors reaching up to 35%, exceeding typical business margins. A comparative analysis in the construction industry highlights discrepancies of 10% to 35% between traditional and AI-driven models. The study concludes that universal AI algorithms often fail to account for industry-specific dynamics, leading to inaccurate evaluations. The practical significance of this research lies in proposing an alternative approach that combines traditional evaluation methods with AI-based tools, offering a more reliable framework for assessing campaign effectiveness | ||
| کلیدواژهها | ||
| Efficiency؛ Artificial Intelligence؛ Advertising Service؛ Google Ads؛ Advertising | ||
| مراجع | ||
|
Androshchuk, H. O. (2019). Tendencies in the development of artificial intelligence technologies: Economic and legal aspects. Teoriia i praktyka intelektualnoi vlasnosti, (3), 84-101.
Authority Hacker. (2023). The state of AI in the online marketing industry: 2023 report. https://www.authorityhacker.com/ai-survey
Babenko, V., Chebanova, N., Ryzhikova, N., Rudenko, S., & Birchenko, N. (2018). Research into the process of multi-level management of enterprise production activities with taking risks into consideration. Eastern-European Journal of Enterprise Technologies, 1(3), 4-12. https://doi.org/10.15587/1729-4061.2018.123461
Babenko, V., Pasmor, M., Pankova, Y., & Sidorov, M. (2017). The place and perspectives of Ukraine in international integration space. Problems and Perspectives in Management, 15(1), 80-92. http://dx.doi.org/10.21511/ppm.15(1).2017.08
Babenko, V., Pravotorova, O., Yefremova, N., Popova, S., Kazanchuk, I., & Honcharenko, V. (2020). The innovation development in China in the context of globalization. WSEAS Transactions on Business and Economics, 17, Art. #25, 523-531. https://doi.org/10.37394/23207.2020.17.51
Babenko, V., Romanenkov, Y., Yakymova, L., & Nakisko, A. (2017). Development of the model of minimax adaptive management of innovative processes at an enterprise with consideration of risks. Eastern-European Journal of Enterprise Technologies, 5(4), 49-56. https://doi.org/10.15587/1729-4061.2017.112076
Batareiev, V. V. (2021). Methods and systems of artificial intelligence. Visnyk of Khmelnytskyi National University, 1(293), 17-21.
Everest-AI Review. (2018). Artificial intelligence for Ukraine – Strength and ability. https://www.everest.ua/wp-content/uploads/2019/01/Everest-AI-Review-%E2%84%965.pdf
Hrabovskyi, Y., Babenko, V., Al’boschiy, O., & Gerasimenko, V. (2020). Development of a technology for automation of work with sources of information on the Internet. WSEAS Transactions on Business and Economics, 17(25), 231-240. https://doi.org/10.37394/23207.2020.17.25
Korinek, A., & Stiglitz, J. E. (2017). Artificial intelligence, worker‐replacing technological change, and income distribution (Working Paper No. 28453). National Bureau of Economic Research. https://www.nber.org/system/files/working_papers/w24174/w24174.pdf
Kotler, P., Kartajaya, H., & Setiawan, I. (2016). Marketing 4.0: Moving from traditional to digital (1st ed.). John Wiley & Sons, Inc.
McKinsey & Company. (2023, June 14). The economic potential of generative AI: The next productivity frontier. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier#introduction
Nestorenko, T., Nestorenko, O., Morkūnas, M., Volkov, A., Baležentis, T., & Štreimikienė, D. (2022). Optimization of production decisions under resource constraints and community priorities. Journal of Global Information Management, 30(12), 1-24. https://doi.org/10.4018/JGIM.304066
Oklander, M., Chukurna, O., Oklander, T., & Yashkina, O. (2020). Methodical principles to calculation information value in pricing policy in supply chains. Estudios de Economía Aplicada, 38(3), 1. http://ojs.ual.es/ojs/index.php/eea/article/view/4009/4263
Pizhuk, O. I. (2019). Shtuchnyj intelekt, jak odyn z kljuchevyh draiverov cyfrovoi transformacii ekonomiki [Artificial intelligence as one of the key drivers of digital transformation of the economy]. Economics, Management and Administration, 3(89), 41-46.
Pradeep, A. K., Appel, A., & Sthanunathan, S. (2019). AI for marketing and product innovation: Powerful new tools for predicting trends, connecting with customers, and closing sales. Wiley.
Simon, H. A. (2019). The sciences of the artificial. MIT Press. https://direct.mit.edu/books/monograph/4551/The-Sciences-of-the-Artificial
Sterne, J. (2017). Artificial intelligence for marketing: Practical applications. John Wiley & Sons, Inc.
Skitsko, O., Skladannyi, P., Shirshov, R., Humeniuk, M., & Vorokhob, M. (2023). Threats and risks of artificial intelligence usage. Cybersecurity: Education, Science, Technique, 2(22), 6-18.
Kabbas, A., Alharthi, A., & Munshi, A. (2020). Artificial intelligence applications in cybersecurity. IJCSNS International Journal of Computer Science and Network Security, 20(2), 120-124.
Savchenko, V. A., & Shapovalenko, O. D. (2020). The main areas of artificial intelligence technologies in cybersecurity. Suchasnyj zahyat informacii [Current Information Security], 4(44), 6-11. https://doi.org/10.31673/2409-7292.2020.040611
Shevchenko, A. (Ed.). (2023). Strategy for artificial intelligence development in Ukraine: Monograph. IAIP. https://doi.org/10.15407/development_strategy_2023
Utkina, M. S., & Shcherbak, N. M. (2021). Theoretical and methodological approaches to the definition of artificial intelligence. Legal Scientific Electronic Journal, (2), 214-217.
| ||
|
آمار تعداد مشاهده مقاله: 105 تعداد دریافت فایل اصل مقاله: 93 |
||