The Relationship Between Consumer Behavior and Purchase Decision Based on Big Data Analyse
Keywords:
big data, consumer behavior, purchase decision, marketing, online platforms
Abstract
This paper tests that sellers can promote the purchase decision of consumers by using big data analysis to detect the consumer behavior. It uses an experimental research design to collect and analyze data from online experiments with consumers who were interested in buying a product or service, and from various online platforms that provide big data on consumer behavior and purchase decision in marketing. The paper finds that sellers who use big data analysis to detect the consumer behavior and tailor their marketing strategies accordingly can significantly increase the purchase decision of the consumers, and also influence the purchase decision of the consumers differently depending on their demographic and psychographic characteristics, and product preferences. The paper provides useful insights and guidance for sellers who want to leverage big data to improve their marketing strategies and outcomes, and also addresses some of the gaps or limitations in the existing literature on this topic.
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[2] Grewal, D., Roggeveen, A. L., & Nordfält, J. (2020). The future of retailing. Journal of Retailing, 96(1), 1–6. https://doi.org/10.1016/j.jretai.2019.10.008
[3] Kumar, V., Rajan, B., Gupta, S., & Dalla Pozza, I. (2020). Customer engagement in service. Journal of the Academy of Marketing Science, 48(3), 469–505. https://doi.org/10.1007/s11747-019-00623-4
[4] Ashraf, M. U., Khan, S. N., & Ansari, A. A. (2021). Impact of brand awareness and social media content marketing on brand loyalty: The mediating role of brand trust. Journal of Organization and Business, 2(1), 158–165. https://doi.org/10.5281/zenodo.5828452
[5] Fan, S., Lau, R. Y., & Zhao, J. L. (2015). Demystifying big data analytics for business intelligence through the lens of marketing mix. Big Data Research, 2(1), 28–32. https://doi.org/10.1016/j.bdr.2015.02.006
[6] Wang, R., & Chan-Olmsted, S. (2020). Content marketing strategy of branded YouTube channels. Journal of Media Business Studies, 17(3), 166–187. https://doi.org/10.1080/16522354.2020.1779510
[7] Habib, S., & Hamadneh, N. N. (2021). Impact of perceived risk on consumers' technology acceptance in online grocery adoption amid COVID-19 pandemic. Sustainability, 13(18), 10221. https://doi.org/10.3390/su131810221MDPI
[8] Lee, C.-H., & Chen, C.-W. (2021). Impulse buying behaviors in live streaming commerce based on the stimulus-organism-response framework. Information, 12(6), 241. https://doi.org/10.3390/info12060241MDPI
[9] Borg, D., Mont, O., & Schoonover, H. (2020). Consumer acceptance and value in use-oriented product-service systems: Lessons from Swedish consumer goods companies. Sustainability, 12(19), 8079. https://doi.org/10.3390/su12198079
[10] Makhitha, K. M., & Ngobeni, K. (2021). The influence of demographic factors on perceived risks affecting attitude towards online shopping. South African Journal of Information Management, 23(1), a1283. https://doi.org/10.4102/sajim.v23i1.1283sajim.co.za+1sajim.co.za+1
[11] Shukla, M., Jain, V., & Misra, R. (2022). Factors influencing smartphone based online shopping: An empirical study of young women shoppers. Asia Pacific Journal of Marketing and Logistics, 34(5), 1060–1077. https://doi.org/10.1108/APJML-01-2021-0042
[12] Gao, Y. (2015). Exploration of digital media marketing mode in the era of big data—Taking Netease News Client as an example. Operation Manager, 2015(10), 1. https://doi.org/10.3969/j.issn.1674-3279.2015.10.228
[13] Xie, K., Hu, Y., & Xiao, J. (2024). Big data-driven innovation in business-user interaction: Theoretical framework and frontier issues. Research and Development Management, 36(1), 147–161. https://doi.org/10.13581/j.cnki.rdm.2024.01.017
[14] Wang, W. (2015). Research on online precision marketing of Haier Group based on user big data [Master's thesis, Northeast Agricultural University]. https://doi.org/10.7666/d.Y2954917
[15] Jiang, L. (2021). Research on the influence of user perceived value on the purchase decision of Jiangsu mobile e-commerce users and management countermeasures under the background of big data. Business Economy, 2021(4), 18–20. https://doi.org/10.3969/j.issn.1009-6043.2021.04.018
[16] Yan, Y., & Cheng, J. (2024). Research application of managerial economics in business management of the examination industry. E-Commerce Letters, 13, 465. https://doi.org/10.3969/j.issn.1672-5939.2024.13.465
[17] Zheng, X. (2024). Research on enterprise refined marketing strategy driven by big data. Modern Economic Management, 5(6), 24–26. https://doi.org/10.3969/j.issn.1673-9108.2024.06.008
[18] Yang, G., Zhang, P., & Liu, M. (2024). Research on the optimization of the operating environment and marketing strategy of Hebei air passenger transportation market. Modern Marketing, 2024(14), 122. https://doi.org/10.3969/j.issn.1673-5587.2024.14.122
[19] Zhang, Y., Dong, Z., & Meng, X. (2021). Research on personalized advertisement recommendation system and its application. Journal of Computer Science, 44(3), 531–563. https://doi.org/10.11896/jsj.202103006
[20] Hu, D., & Xia, J. (2023). Theoretical logic and policy framework of data as a core element. Journal of Xi'an Jiaotong University (Social Sciences), 43(2), 1–10. https://doi.org/10.3969/j.issn.1001-4527.2023.02.001
[21] Li, P. (2024). Research on privacy protection in the era of big data. Open Journal of Legal Science, 12, 4400. https://doi.org/10.4236/ojls.2024.124020
[22] Luo, L. (2024). How virtual reality promotes the new development of e-commerce: A perspective of “human-technology” relationship theory. E-Commerce Letters, 13, 7886. https://doi.org/10.3969/j.issn.1672-5939.2024.13.7886
[23] Tafesse, W., & Wood, B. P. (2021). Followers’ engagement with Instagram influencers: The role of influencers’ content and engagement strategy. Journal of Retailing and Consumer Services, 58, 102303. https://doi.org/10.1016/j.jretconser.2020.102303
[24] Khamis, S., Ang, L., & Welling, R. (2017). Self-branding, ‘micro-celebrity’ and the rise of social media influencers. Celebrity Studies, 8(2), 191–208. https://doi.org/10.1080/19392397.2016.1218292
[25] Kim, D. Y., & Kim, H. Y. (2020). Influencer advertising on social media: The multiple inference model on influencer–product congruence and sponsorship disclosure. Journal of Business Research, 130, 405–415. https://doi.org/10.1016/j.jbusres.2020.02.033
[26] Yoshida, M., Gordon, B. S., & James, J. D. (2021). Social capital and consumer happiness: Toward an alternative explanation of consumer–brand identification. Journal of Brand Management, 28(5), 481–494. https://doi.org/10.1057/s41262-021-00231-1
[27] Vazquez, D., Wu, X., Nguyen, B., Kent, A., Gutierrez, A., & Chen, T. (2020). Investigating narrative involvement, parasocial interactions, and impulse buying behaviours within a second screen social commerce context. International Journal of Information Management, 53, 102135. https://doi.org/10.1016/j.ijinfomgt.2020.102135
[28] Gawron, M., & Strzelecki, A. (2021). Consumers’ adoption and use of e-currencies in virtual markets in the context of an online game. Journal of Theoretical and Applied Electronic Commerce Research, 16(6), 1266–1279. https://doi.org/10.3390/jtaer16060070
[29] Chen, G., Zeng, D., Wei, Q., et al. (2020). Decision-making paradigm shift and enabling innovation in big data environment. Management World, 36(2), 95–105. https://doi.org/10.19744/j.cnki.11-1235/f.2020.0029
[30] Quan, F. (2024). A study of the impact of virtual networks in marketing. E-Commerce Letters, 13, 5242. DOI: CNKI:SUN:DZWL.0.2024-13-062
[31] Feng, Z., Guo, X., Zeng, D., et al. (2013). Frontiers of business management research in the context of big data①. Journal of Management Science, 16(1), 1–12. DOI: CNKI:SUN:GLKX.0.2013-01-001
[32] Pu, Z., Zhang, C., & Xu, Z. (2025). A review of consumer preference mining research based on online reviews. China Management Science, 33(1), 209–220. https://doi.org/10.16381/j.cnki.issn1003-207x.2025.01.020
[33] Jin, W. (2024). Research on the application of big data technology in the field of e-commerce marketing. E-Commerce Letters, 13, 5940. DOI: CNKI:SUN:DZWL.0.2024-13-071
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2025-04-30
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