Abstract
This paper explores the application of Big Data in crafting marketing tactics amid the digital transformation of the economy. Significant focus is given to analytical methods for handling large data collections, procedures for their deployment in customer segmentation, tailoring marketing promotions, and predicting market actions. This research aims to examine the potential for utilizing Big Data in marketing endeavors and to validate its importance in boosting the effectiveness of creating and executing contemporary marketing plans. Throughout the scholarly investigation, standard scientific techniques of examination and combination were employed to examine the conceptual basis of Big Data and its function in promotional endeavors, comparison – to contrast various analytical strategies and information handling methods, generalization – to shape main findings concerning the utilization of big data in formulating marketing tactics, and a systemic perspective – to view Big Data as a unified instrument for overseeing promotional operations. The theoretical underpinnings of Big Data are characterized, and its function in contemporary marketing operations is determined. The principal origins of marketing information and techniques for their gathering in the digital economy are examined. Analytical methods for handling Big Data (descriptive, diagnostic, predictive, and prescriptive analytics) are investigated. The instruments and technologies employed to examine big data in marketing are pinpointed. The effect of Big Data on shaping marketing plans is analyzed, especially regarding segmentation, personalization, and anticipating shopper conduct. The core challenges and constraints of deploying Big Data in marketing endeavors are identified. The potential for advancing the application of Big Data in strategic marketing administration is described. It is demonstrated that these actions aid in boosting the efficacy of marketing plans through more precise partitioning of customers, a richer grasp of their actions, a swift reaction to shifts in market environments, and an elevation in the degree of customization for marketing interactions.
References
1. Lehenchuk, S. F., & Zavalii, T. O. (2023). Big Data v marketynhovii analitytsi: mozhlyvosti ta problemy vykorystannia [Big Data in marketing analytics: opportunities and challenges of use]. Problemy teorii ta metodolohii bukhhalterskoho obliku, kontroliu i analizu, 1(54), 52–58. https://doi.org/10.26642/pbo-2023-1(54)-52-58 (in Ukrainian)
2. Stankevych, I. V., Sakun, H. O., & Sakun, O. V. (2023). Sotsialno-ekonomichnyi fenomen “velykykh danykh” v stratehii tsyfrovoho marketynhu [The socio-economic phenomenon of “big data” in digital marketing strategy]. Visnyk KhNTU, 2(85), 235–239. https://doi.org/10.35546/kntu2078-4481.2023.2.33 (in Ukrainian)
3. Cherniavska, O., & Kaznodii, V. (2023). The innovative marketing management systems in digitalization conditions. Management, 38(2), 96–106. https://doi.org/10.30857/2415-3206.2023.2.8
4. Lutsii, O., & Helevei, O. (2023). Formuvannia komponentiv marketynhovoi informatsiinoi systemy dlia silskohospodarskoi produktsii za dopomohoiu metodiv Big Data [Formation of components of a marketing information system for agricultural products using Big Data methods]. Oblik i finansy, 3(101), 145–150. https://doi.org/10.33146/2307-9878-2023-3(101)-145-151 (in Ukrainian)
5. Maranchak, N. (2023). Vykorystannia shtuchnoho intelektu v tsyfrovomu marketynhu bibliotechnoi haluzi Ukrainy: zarubizhnyi dosvid i perspektyvy [Using artificial intelligence in digital marketing of the library industry in Ukraine: foreign experience and prospects]. Tsyfrova platforma: informatsiini tekhnolohii v sotsiokulturnii sferi, 6(1), 172–184. https://doi.org/10.31866/2617-796X.6.1.2023.283986 (in Ukrainian)
6. Liu, Q., Wang, R., Pareti, M., Castellini, A., Viaggi, D., & Canavari, M. (2026). Big data in consumer behavior research: A systematic review of data sources, analytical methods, and research questions. Journal of Marketing Analytics. https://doi.org/10.1057/s41270-026-00470-6
7. Theodorakopoulos, L., Theodoropoulou, A., & Klavdianos, с. (2026). Big data analytics and AI for consumer behavior in digital marketing: Applications, synthetic and dark data, and future directions. Big Data and Cognitive Computing, 10(2), 46. https://doi.org/10.3390/bdcc10020046
8. Ye, С. (2024). The current state of big data analytics research in marketing: A systematic review using TCCM approach. Journal of Global Scholars of Marketing Science, 34(3), 393–415. https://doi.org/10.1080/21639159.2023.2275792
9. Zhang, H., & Song, M. (2022). How big data analytics, AI, and social media marketing research boost market orientation. Research-Technology Management, 65(2), 64–70. https://doi.org/10.1080/08956308.2022.2022907
10. Boegershausen, J., Datta, H., Borah, A., & Stephen, A. T. (2022). Fields of gold: Scraping web data for marketing insights. Journal of Marketing, 86(5), 1–20. https://doi.org/10.1177/00222429221100750
11. Dong, S., Xiao, L., & Kwon, J. (2026). Emerging Frontiers in Marketing: Exploring the Potential of Novel Data and Methodologies. Australasian Marketing Journal, 34(2), 117–119. https://doi.org/10.1177/14413582261420453
12. Shymko, A. (2024). Vplyv tsyfrovoho marketynhu u sotsialnykh merezhakh na kupivelni namiry spozhyvachiv [The impact of digital marketing on social media on consumer purchasing intentions]. Visnyk Chernivetskoho torhovelno-ekonomichnoho instytutu, 4(96), 191–209. http://doi.org/10.34025/2310-8185-2024-4.96.12 (in Ukrainian)
13. Roy, D., Srivastava, R., Jat, M., & Karaca, M. S. (2022). A complete overview of analytics techniques: Descriptive, predictive, and prescriptive. In P. M. Jeyanthi, T. Choudhury, D. Hack-Polay, T. P. Singh, & S. Abujar (Eds.), Decision Intelligence Analytics and the Implementation of Strategic Business Management. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-82763-2_2
14. Wolniak, R. (2023). The concept of descriptive analytics. Scientific Papers of Silesian University of Technology. Organization and Management, (172), 699–715. http://dx.doi.org/10.29119/1641-3466.2023.172.42
15. Jamarani, A., Haddadi, S., Sarvizadeh, R., Kashani, M. H., Akbari, M., & Moradi, S. (2024). Big data and predictive analytics: A systematic review of applications. Artificial Intelligence Review, (57), Article 176. https://doi.org/10.1007/s10462-024-10811-5
16. Vishwakarma, K., Kaur, J., & Soni, G. (2025). A comparative study of big data analytics tools: Hadoop, Spark, TensorFlow, SAS, and Tableau in modern data pipelines. International Journal for Research in Applied Science & Engineering Technology (IJRASET), 13(V), 1948–1953. https://doi.org/10.22214/ijraset.2025.70585
17. Belcastro, L., Cantini, R., Marozzo, F., Orsino, A., Talia, D., & Trunfio, P. (2022). Programming big data analysis: principles and solutions. Journal of Big Data, (9), Article 4. https://doi.org/10.1186/s40537-021-00555-2
18. Abdalla, H. B. (2022). A brief survey on big data: technologies, terminologies and data-intensive applications. Journal of Big Data, (9), Article 107. https://doi.org/10.1186/s40537-022-00659-3
19. Shymko, A. V., Zamialyi, D. V., & Kizenko, S. H. (2025). Analiz vprovadzhennia innovatsiinykh metodiv prosuvannia produktsii u sferi elektronnoi komertsii Ukrainy [Analysis of the implementation of innovative methods of product promotion in the e-commerce sector of Ukraine]. Aktualni pytannia ekonomichnykh nauk, (10). https://doi.org/10.5281/zenodo.15256942 (in Ukrainian)
20. Liu, H., Tan, K. H., & Pawar, K. (2022). Predicting viewer gifting behavior in sports live streaming platforms: The impact of viewer perception and satisfaction. Journal of Business Research, (144), 599–613. https://doi.org/10.1016/j.jbusres.2022.02.045
21. Lehenchuk, S. F., & Zavalii, T. O. (2023). Big Data v marketynhovii analitytsi: mozhlyvosti ta problemy vykorystannia [Big Data in marketing analytics: opportunities and challenges of use]. Problemy teorii ta metodolohii bukhhalterskoho obliku, kontroliu i analizu, 1(54), 52–58. https://doi.org/10.26642/pbo-2023-1(54)-52-58 (in Ukrainian)
22. Vdovichena, O., Krymska, A., Koroliuk, Y., Shymko, A., & Vdovichen, A. (2025). The role of artificial intelligence technologies in rebuilding the post-war economy and ensuring cyber security: an example from Ukraine. Salud, Ciencia y Tecnología – Serie de Conferencias, (4), 642. https://doi.org/10.56294/sctconf2025642
23. Vdovichena, O., Krymska, A., Koroliuk, Y., Shymko, A., & Vdovichen, A. (2024). Digital technologies and cybersecurity in the strategy of post-war economic recovery. Economic Affairs, 69(03), 1557–1568. https://doi.org/10.46852/0424-2513.4.2024.38
24. Zaitseva, O., Zhosan, H., & Chyzhova, Yu. (2025). BIG DATA yak rushiina syla stratehii tsyfrovoho marketynhu [BIG DATA as a driving force of digital marketing strategies]. Tavriiskyi naukovyi visnyk. Seriia: Ekonomika, (24), 271–277. https://doi.org/10.32782/2708-0366/2025.24.29 (in Ukrainian)
25. Bondarenko, V., & Omelianenko, O. (2024). Vplyv shtuchnoho intelektu (AI) na rozvytok internet-marketynhu [The impact of artificial intelligence (AI) on the development of online marketing]. Herald of Khmelnytskyi National University. Economic Sciences, 334(5), 319–324. https://doi.org/10.31891/2307-5740-2024-334-47 (in Ukrainian)
26. Zatonatska, T., et al. (2022). Forecasting the Behavior of Target Segments to Activate Advertising Tools: Case of Mobile Operator Vodafone Ukraine. Economics, 10(1), 87–104. https://doi.org/10.2478/eoik-2022-0005
27. Vdovichena, O. H., Vdovichen, D. A., & Pichyk, K. V. (2025). Vykorystannia BIG DATA dlia prohnozuvannia efektyvnosti marketynhovykh kampanii u realnomu chasi [Using BIG DATA to predict the effectiveness of marketing campaigns in real time]. Aktualni pytannia ekonomichnykh nauk, (17). https://doi.org/10.5281/zenodo.17573391 (in Ukrainian)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright (c) 2026 Alla Shymko, Anatolii Vdovichen, Iryna Losheniuk