Home / Current Issue / Paper 1714891
Exploring the Impact of Big Data on Social Media Marketing Practices Among Major UK Retailers
Subject area: Management and Commerce · Area of research: Business Analytics
Abstract
This study explores the impact of big data analytics on social media marketing practices among major UK retailers, focusing on platforms such as Facebook, Instagram, Twitter, and YouTube. The research examines how these companies leverage big data to optimise marketing strategies, enhance customer engagement, and improve return on investment (ROI). Employing a quantitative survey methodology integrated with semi-structured interviews with marketing professionals in the tech and retail sectors, the study adopts a positivist philosophy with a deductive approach underpinned by the Technology Acceptance Model (TAM) and Diffusion of Innovations (DOI) theory. Key findings reveal a strong positive correlation (r = 0.65) between big data usage and customer engagement, with regression analysis showing that big data analytics explains 45% of the variance in marketing ROI (β = 0.68, p < 0.001). Case studies of ASOS, Next, and Boots demonstrate practical applications including sentiment analysis, predictive analytics, and cross-platform data integration. The study also highlights significant challenges in data privacy and ethical considerations, suggesting that future adoption of big data analytics in marketing requires a balance between technological advancement and consumer trust. Recommendations include investing in advanced analytics tools, staff training, and cultivating a data-driven culture to maintain competitiveness.
Keywords
Big Data Analytics, Customer Engagement, Return on Investment, Social Media Marketing, UK Retail
References
[1] X. Liu, H. Shin, and A. C. Burns, “Examining the impact of luxury brand’s social media marketing on customer engagement: Using big data analytics and natural language processing,” Journal of Business Research, vol. 125, pp. 815–826, 2021.
[2] U. Sivarajah et al., “Critical analysis of big data challenges and analytical methods,” Journal of Business Research, vol. 70, pp. 263–286, 2020.
[3] V. Jafari-Sadeghi et al., “Exploring the impact of digital transformation on technology entrepreneurship,” Journal of Business Research, vol. 124, pp. 100–111, 2021.
[4] N. Stylos et al., “Big data analytics and consumer behaviour in tourism and hospitality,” 2021.
[5] J. Abbas et al., “Exploring the impact of COVID-19 on tourism: transformational potential and implications,” Current Research in Behavioral Sciences, vol. 2, p. 100033, 2021.
[6] S. Hussain et al., “Examining the effects of celebrity trust on advertising credibility,” Journal of Business Research, vol. 109, pp. 472–488, 2020.
[7] L. J. Menzli et al., “Investigation of open educational resources adoption using Rogers’ diffusion of innovation theory,” Heliyon, vol. 8, no. 7, 2022.
[8] A. S. Al Teneiji, T. Y. A. Salim, and Z. Riaz, “Factors impacting adoption of big data in healthcare,” International Journal of Medical Informatics, p. 105460, 2024.
[9] B. Al-Ateeq et al., “Big data analytics in auditing using the TAM,” Corporate Governance and Organisational Behavior Review, vol. 6, no. 1, pp. 64–78, 2022.
[10] S. F. Chou et al., “Identifying critical factors for sustainable marketing in catering,” Journal of Hospitality and Tourism Management, vol. 51, pp. 11–21, 2022.
[11] J. V. D. S. Meira and M. Hancer, “Using the social exchange theory to explore the employee-organisation relationship,” International Journal of Contemporary Hospitality Management, vol. 33, no. 2, pp. 670–692, 2021.
[12] N. Zaman et al., “Trends and future perspective challenges in big data,” in Advances in Intelligent Data Analysis and Applications, Springer, pp. 309–325, 2021.
[13] S. Mohr and R. Kühl, “Acceptance of artificial intelligence in German agriculture: TAM and TPB,” Precision Agriculture, vol. 22, no. 6, pp. 1816–1844, 2021.
[14] S. Kamboj and S. Rana, “Big data-driven supply chain and performance: A resource-based view,” The TQM Journal, vol. 35, no. 1, pp. 5–23, 2023.
[15] M. Hussain et al., “Challenges of big data analytics for sustainable supply chains in healthcare: A resource-based view,” Benchmarking: An International Journal, 2023.
[16] M. Holmlund et al., “Customer experience management in the age of big data analytics,” Journal of Business Research, vol. 116, pp. 356–365, 2020.
[17] H. Hassani et al., “Text mining in big data analytics,” Big Data and Cognitive Computing, vol. 4, no. 1, p. 1, 2020.
[18] X. Liu, H. Shin, and A. C. Burns, “Examining the impact of luxury brand’s social media marketing on customer engagement,” Journal of Business Research, vol. 125, pp. 815–826, 2021.
[19] G. Kostygina et al., “Boosting health campaign reach through social media influencers,” Social Media + Society, vol. 6, no. 2, 2020.
[20] S. S. Kamble et al., “A performance measurement system for industry 4.0 enabled smart manufacturing,” International Journal of Production Economics, vol. 229, p. 107853, 2020.
[21] M. Naeem et al., “Trends and future perspective challenges in big data,” in Advances in Intelligent Data Analysis and Applications, Springer, pp. 309–325, 2022.
[22] F. Caputo et al., “Over the mask of innovation management in the world of big data,” Journal of Business Research, vol. 119, pp. 330–338, 2020.
[23] L. Dolega, F. Rowe, and E. Branagan, “Going digital? The impact of social media marketing on retail website traffic,” Journal of Retailing and Consumer Services, vol. 60, p. 102501, 2021.
[24] W. N. Wassouf et al., “Data privacy and ethical considerations in big data analytics,” 2020.
[25] S. Bresciani et al., “Using big data for co-innovation processes,” International Journal of Information Management, vol. 60, p. 102347, 2021.
[26] Y. Kim, “Organisational resilience and employee work-role performance after a crisis,” Journal of Public Relations Research, vol. 32, no. 1–2, pp. 47–75, 2020.
[27] J. R. Saura, D. Ribeiro-Soriano, and D. Palacios-Marqués, “Setting B2B digital marketing in AI-based CRMs,” Industrial Marketing Management, 2021.
[28] R. J. Limaye et al., “Social media strategies to affect vaccine acceptance: A systematic review,” Expert Review of Vaccines, vol. 20, no. 8, pp. 959–973, 2021.
[29] P. Maroufkhani et al., “Big data analytics adoption: Determinants and performances among SMEs,” International Journal of Information Management, vol. 54, p. 102190, 2020.
[30] D. Buhalis, D. Leung, and M. Lin, “Metaverse as a disruptive technology revolutionising tourism,” Tourism Management, vol. 97, p. 104724, 2023.
[31] A. Castillo López, F. J. Llorens Montes, and J. Braojos Gómez, “Impact of social media on the firm’s knowledge exploration,” Association for Information Systems, 2021.
[32] Y. K. Dwivedi et al., “Setting the future of digital and social media marketing research,” International Journal of Information Management, vol. 59, p. 102168, 2021.
[33] P. Mikalef et al., “Exploring the relationship between big data analytics capability and competitive performance,” Information & Management, vol. 57, no. 2, p. 103169, 2020.
[34] F. Cappa et al., “Big data for creating and capturing value in the digitalised environment,” Journal of Product Innovation Management, vol. 38, no. 1, pp. 49–67, 2021.
[35] P. Garg et al., “Examining the relationship between social media analytics practices and business performance,” International Journal of Information Management, vol. 52, p. 102069, 2020.
How to cite this paper
@article{1714891,
author = {Favour Oluchi Amede},
title = {Exploring the Impact of Big Data on Social Media Marketing Practices Among Major UK Retailers},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {9},
pages = {976-983},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1714891.pdf},
abstract = {This study explores the impact of big data analytics on social media marketing practices among major UK retailers, focusing on platforms such as Facebook, Instagram, Twitter, and YouTube. The research examines how these companies leverage big data to optimise marketing strategies, enhance customer engagement, and improve return on investment (ROI). Employing a quantitative survey methodology integrated with semi-structured interviews with marketing professionals in the tech and retail sectors, the study adopts a positivist philosophy with a deductive approach underpinned by the Technology Acceptance Model (TAM) and Diffusion of Innovations (DOI) theory. Key findings reveal a strong positive correlation (r = 0.65) between big data usage and customer engagement, with regression analysis showing that big data analytics explains 45% of the variance in marketing ROI (β = 0.68, p < 0.001). Case studies of ASOS, Next, and Boots demonstrate practical applications including sentiment analysis, predictive analytics, and cross-platform data integration. The study also highlights significant challenges in data privacy and ethical considerations, suggesting that future adoption of big data analytics in marketing requires a balance between technological advancement and consumer trust. Recommendations include investing in advanced analytics tools, staff training, and cultivating a data-driven culture to maintain competitiveness.},
keywords = {Big Data Analytics, Customer Engagement, Return on Investment, Social Media Marketing, UK Retail},
month = {March},
doi = {https://doi.org/10.64388/IREV9I9-1714891}
}