The critical role that big data analytics (BDA) plays for enhancing marketing strategies in a variety of industries is examined in this article. Gaining a competitive edge now requires integrating BDA into marketing frameworks since businesses depend more and more on data-driven decision-making. The literature on BDA applications in marketing is summarized in this review, which also looks at how data collection, processing, and analysis affect customer insights, segmentation, personalization, and campaign efficacy. A thorough systematic literature review (SLR) was conducted, and PRISMA was used for a thorough sample selection process. Out of the 150 articles that were initially found, 100 were eliminated since they did not fit the inclusion requirements. Ultimately, 50 publications that satisfied the inclusion requirements were used in this study. According to the results, BDA helps marketers to increase customer engagement (30%), optimize resource allocation (34%), and improve return on investment (ROI) (36%), which is thought to be the most significant contributor through targeted strategies. The review also identifies obstacles, such as the requirement for qualified staff and data protection issues, and makes suggestions for future research directions. All things considered, this study emphasizes how big data analytics can revolutionize contemporary marketing tactics.

1. Sheng J, Amankwah-amoah J, Khan Z, & Wang X. COVID-19 Pandemic in the New Era of Big Data Analytics: Methodological Innovations and Future Research Directions. British journal of management. 2021, 32(4): 1164–1183. doi: 10.1111/1467-8551.12441

2. Mayer-Schönberger V, & Cukier K. Big data: A revolution that will transform how we live, work, and think. Houghton Mifflin Harcourt; 2013.

3. Amellal I, Amellal A, Seghiouer H, & Ech-charrat MR. An integrated approach for modern supply chain management: Utilizing advanced machine learning models for sentiment analysis, demand forecasting, and probabilistic price prediction. Decision Science Letters. 2024; 13(2024): 237–248. doi: 10.5267/dsl.2023.9.003

4. Baryannis G, Validi S, Dani S, & Antoniou G. Supply chain risk management and artificial intelligence: state of the art and future research directions. International Journal of Production Research. 2019; 57(7): 2179–2202. doi: 10.1080/00207543.2018.1530476

5. Chen H, Chiang RHL, & Storey VC. Business intelligence and analytics: From big data to big impact. MIS Quarterly. 2012; 36(4): 1165–1188. doi: 10.2307/41703503

6. Kumar V, Dixit A, & Singh R. The role of big data analytics in enhancing marketing strategies: A case study of Indian retail sector. International Journal of Retail & Distribution Management. 2016; 44(7): 758–774. doi: 10.1108/IJRDM-04-2015-0051

7. Naz F, Kumar A, Majumdar A, & Agrawal R. Is artificial intelligence an enabler of supply chain resiliency post COVID-19? An exploratory state-of-the-art review for future research. Operations Management Research. 2022; 15(1–2): 378–398. doi: 10.1007/s12063-021-00208-w

8. Abraham A, & Ghosh S. Big data analytics in marketing: A systematic review of the literature. Journal of Business Research. 2020; 116: 128–139. doi: 10.1016/j.jbusres.2018.10.012

9. Data-Driven Marketing Association (DDMA). The ROI of Data-Driven Marketing. Available online: https://www.ddma.nl (accessed on 2 November 2024).

10. Harris LC, & Ogbonna E. A data-driven approach to marketing strategy. Journal of Business Research. 2018; 85: 10–20. doi: 10.1016/j.jbusres.2017.12.067

11. Lemon KN, & Verhoef PC. Understanding customer experience throughout the customer journey. Journal of Marketing. 2016; 80(6): 69–96. doi: 10.1509/jm.15.0420

12. Chaffey D. Digital marketing: Strategy, implementation, and practice. Pearson; 2023.

13. Hassan LM, & Shiu EM. The impact of big data analytics on marketing performance: A systematic review and future research directions. Journal of Business Research. 2019; 100: 234–249. doi: 10.1016/j.jbusres.2018.12.062

14. Ashiru F, Adegbite E, Nakpodia F, & Koporcic N. Relational governance mechanisms as enablers of dynamic capabilities in Nigerian SMEs during the COVID-19 crisis. Industrial Marketing Management. 2022; 105: 18–32. doi: 10.1016/j.indmarman.2022.05.011

15. Grover V, Chiang RHL, Liang TP, & Zhang DJ. Creating strategic business value from big data analytics: A research framework. Journal of Management Information Systems. 2018; 35(2): 388–423. doi: 10.1080/07421222.2018.1451951

16. Awan U, & Awan F. Big data analytics in marketing: A comprehensive review. International Journal of Information Management. 2021; 57: 102–113. doi: 10.1016/j.ijinfomgt.2020.102113

17. Chahal H, Punia BK, & Kaur M. Big data analytics in marketing: A review of the literature and future research directions. Journal of Business Research. 2020; 116: 251–264. doi: 10.1016/j.jbusres.2019.11.024

18. Barbeiro L, Gomes A, Correia FB, et al. A Review of Educational Data Mining Trends. Procedia Computer Science. 2024; 237: 88–95. doi: 10.1016/j.procs.2024.05.0813

19. Dillman DA, Smyth JD, & Christian LM. Internet, phone, mail, and mixed-mode surveys: The tailored design method. Wiley; 2017.

20. Bennett R, & Rundle-Thiele S. The role of big data in enhancing marketing strategies: A systematic review of the literature. Journal of Marketing Management. 2019; 35(1–2): 104–127. doi: 10.1080/0267257X.2018.1541945

21. Clifton B. Advanced web metrics with Google Analytics. Wiley; 2020.

22. Shehu ZY, Musa MN, Ahmed AA, & Bashir ZS. Social Media and Business Practices: Who is Following Who and Why? In: Proceedings of Bilsel International Truva Scientific Researches and Innovation Congress; 25–26 August 2023; İZMİR, Türkiye. pp. 573–587.

23. Meyer M, Schubert T, & Huber M. The role of big data analytics in marketing: A systematic literature review. Journal of Business Research. 2020; 116: 1–12. doi: 10.1016/j.jbusres.2019.10.045

24. Chauhan S, & Jha P. Big data analytics and digital marketing: A systematic review of literature and future research directions. Journal of Marketing Management. 2021; 37(9–10): 1122–1143. doi: 10.1080/0267257X.2021.1945314

25. Onwuegbuzie AJ, Leech NL, & Collins KMT. A call for qualitative power analyses. Quality & Quantity. 2011; 45(4): 1057–1073. doi: 10.1007/s11135-010-9438-3

26. Bardin L. Content analysis: An introduction to its methodology. Sage Publications; 2016.

27. Tuten TL, & Solomon MR. Social media marketing. Sage; 2017.

28. Gomez-Uribe CA, & Hunt N. The Netflix recommendation system: Algorithms, business value, and innovation. ACM Transactions on Management Information Systems. 2016; 6(4): 1–19. doi: 10.1145/2843948

29. Hasan M, Ullah KT, & Bhattacharjee H. Brand Valuation of Commercial Banks in Bangladesh: An Application of Marketing Profitability. Journal of Business Theory and Practice. 2015; 3(2): 159–177.

30. Järvinen JM, Tarkiainen A, & Tobon J. Effectual and causal reasoning in the adoption of marketing automation. Industrial Marketing Management. 2020; 86: 212–222. doi: 10.1016/j.indmarman.2019.12.008

31. Bhatt C, & Zaveri M. Big data analytics: A systematic literature review on techniques and applications. International Journal of Information Management. 2020; 51: 102036. doi: 10.1016/j.ijinfomgt.2019.102036

32. Khan MA, Khan MN, & Rehman A. The impact of big data analytics on firms’ performance: A study of the mediating role of decision-making quality. Journal of Business Research. 2020; 117: 442–454. doi: 10.1016/j.jbusres.2019.11.045

33. Zhang Y, & Zhao X. The impact of big data on marketing strategy: Evidence from the retail industry. Journal of Retailing and Consumer Services. 2019; 51: 123–132. doi: 10.1016/j.jretconser.2019.05.014

34. Chaffey D, & Ellis-Chadwick F. Digital Marketing: Strategy, Implementation and Practice. Pearson Education; 2019.

35. Kumar V, & Reinartz W. Creating enduring customer value. Harvard Business Review Press; 2021.

36. Gupta S, & Lehmann DR. Managing customers as investments: The strategic value of customers in the long run. Wharton School Publishing; 2022.

37. Reichheld FF. The ultimate question 2.0: How net promoter companies thrive in a customer-driven world. Harvard Business Review Press; 2021.

38. Eze SC, & Chinedu-eze VC. Some antecedent factors that shape SMEs adoption of social media marketing applications: a hybrid approach. Journal of Science and Technology Policy Management. 2020; 12(1): 41–61. doi: 10.1108/JSTPM-06-2019-0063

39. Eze SC, Chinedu-eze VCA, Okike CK, & Bello AO. Critical factors influencing the adoption of digital marketing devices by service-oriented micro-businesses in Nigeria: A thematic analysis approach. Humanities and Social Sciences Communications. 2020; 7: 90. doi: 10.1057/s41599-020-00580-1

40. He Y, & Wei Y. Big data analytics and marketing strategy performance: The moderating role of organizational culture. Journal of Business Research. 2021; 124: 576–585. doi: 10.1016/j.jbusres.2020.11.031

41. Hossain MN, & Kaur A. The influence of big data analytics on marketing decision-making: A systematic literature review. Marketing Intelligence & Planning. 2020; 38(3): 451–467. doi: 10.1108/MIP-09-2019-0463

42. Khan MA, Khan MN, & Rehman A. Understanding unstructured data: Concepts and techniques in big data analytics. Journal of Business Research. 2021; 126: 139–151. doi: 10.1016/j.jbusres.2020.12.001

43. Kumar A, Ahmad R, & Mani S. Regulatory compliance and ethical considerations of big data analytics in marketing. Marketing Intelligence & Planning. 2023; 41(2): 215–232. doi: 10.1108/MIP-06-2022-0314

44. Pang C, Liu J, & Zhou Y. Data privacy and consumer trust in the age of big data: A systematic review. Journal of Business Research. 2022; 140: 77–89. doi: 10.1016/j.jbusres.2021.11.043

45. Davenport TH, & Ronanki R. How artificial intelligence will change the future of marketing. Harvard Business Review. 2018; 96(4): 34–43.

46. Sharma S, Wadhwa K, & Gupta A. The role of natural language processing in big data analytics. Journal of Big Data. 2021; 8(1): 1–15. doi: 10.1186/s40537-021-00266-3

47. Wang Y, Kung LA, & Byrd TA. Big data in education: A systematic review of the literature. Computers & Education. 2022; 128: 1–15. doi: 10.1016/j.compedu.2022.104354

48. Singh S, Gupta A, & Sharma R. Challenges in integrating big data analytics into marketing strategies: A review and future research agenda. Journal of Business Research. 2023; 148: 379–391. doi: 10.1016/j.jbusres.2022.05.045

49. Choudhury A, & Kar AK. Small and medium enterprises’ readiness for big data analytics: An empirical investigation. Journal of Small Business Management. 2023; 61(1): 123–145. doi: 10.1080/00472778.2022.2034567

50. Mishra N, & Singh R. Leveraging big data analytics for enhancing customer engagement in SMEs. International Journal of Information Management. 2023; 67: 102–111. doi: 10.1016/j.ijinfomgt.2022.102111

51. Yang Y, & Li Z. Big data analytics in marketing: A systematic review and future research agenda. Journal of Marketing Theory and Practice. 2020; 28(2): 193–206. doi: 10.1080/10696679.2020.1750530