Research on E-commerce User Profile Construction and Personalized Service Strategies Based on Multi-Source Heterogeneous Data
Main Article Content
Abstract
As e-commerce enters an era of intensive competition, data-driven refined operation has become essential for improving service accuracy and user conversion. However, user data are often scattered across different platforms and systems, producing data silos, distorted user profiles, and ineffective recommendations. This study proposes a user profile construction framework based on multi-source heterogeneous data fusion. E-commerce transaction data, behavioral logs, social media content, search records, product information, and customer service records are integrated through data cleaning, entity alignment, and feature fusion. A multidimensional tag system is then constructed from five dimensions: basic attributes, consumption power, interest preference, social relationship, and lifecycle stage. Based on the resulting profiles, dynamic personalized service strategies are designed through user segmentation and recommendation mechanisms, and their effectiveness is verified through A/B testing. The results show that user profiles constructed from multi-source data achieve significantly higher coverage and accuracy than profiles based on a single data source. The study provides an operable framework for overcoming data barriers and upgrading intelligent e-commerce services.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
References
O. Semenda, Y. Sokolova, O. Korovina, et al., “Using social media analysis to improve E-commerce marketing strategies,” International Review of Management and Marketing, vol. 14, no. 4, pp. 61-71, 2024, doi: 10.32479/irmm.16196.
B. Putri L W and T. Setiawan B L, “Analyzing the strategic contribution of social media influencers to e-commerce marketing effectiveness,” JUMDER: Jurnal Bisnis Digital dan Ekonomi Kreatif, vol. 1, no. 2, pp. 12-21, 2025, doi: 10.1234/jumder.v1i2.21.
Y. Wang and R. Guo, “Tourism e-commerce marketing following live-streaming: consumer behavior and verification psychology,” Tourism Review, vol. 80, no. 4, pp. 914-927, 2025, doi: 10.1108/TR-10-2023-0738.
M. Sun and H. Wang, “AI-Powered Customer Engagement Sequence Analysis and Conversion Funnel Optimization in Multi-Channel E-Commerce Marketing,” Journal of Industrial Engineering and Applied Science, vol. 3, no. 5, pp. 7-20, 2025, doi: 10.70393/6a69656173.333138.
J. Wang, “Innovation of e-commerce marketing model under the background of big data and artificial intelligence,” Journal of computational methods in sciences and engineering, vol. 22, no. 5, pp. 1721-1727, 2022, doi: 10.3233/JCM-226152.
A. Zhuk and O. Yatskyi, “The use of artificial intelligence and machine learning in e-commerce marketing,” Technology audit and production reserves, vol. 3, no. 4, pp. 33-38, 2024, doi: 10.15587/2706-5448.2024.305280.
S. Smerichevskyi, A. Kovalchuk, T. Obydiennova, et al., “Development strategies for marketing and logistics in the innovative ecosystem of e-commerce,” Revista Gestão & Tecnologia, vol. 25, no. 2, pp. 90-107, 2025, doi: 10.20397/2177-6652/2025.v25i2.3162.
M. Sakinah and I. Heruwasto, “Pengaruh e-commerce marketing stimuli terhadap trust, customer satisfaction, dan customer loyalty,” Jurnal Samudra Ekonomi dan Bisnis, vol. 15, no. 2, pp. 258-271, 2024, doi: 10.33059/jseb.v15i2.8946.
S. Kalogiannidis, F. A. Kagioglou, and O. Papaevangelou, “Strategic marketing management influence on making e-commerce promotions,” International Journal of Scientific Research and Management, vol. 10, no. 1, pp. 2949-2955, 2022, doi: 10.18535/ijsrm/v10i1.em11.
L. Sanbella, I. Van Versie, and S. Audiah, “Online marketing strategy optimization to increase sales and e-commerce development: An integrated approach in the digital age,” Startupreneur Business Digital (SABDA Journal), vol. 3, no. 1, pp. 54-66, 2024, doi: 10.33050/sabda.v3i1.492.
J. Purnomo Y, “Digital marketing strategy to increase sales conversion on e-commerce platforms,” Journal of Contemporary Administration and Management (ADMAN), vol. 1, no. 2, pp. 54-62, 2023, doi: 10.61100/adman.v1i2.23.
Q. Liu, H. Tang, L. Wu, et al., “Deep learning-driven e-commerce marketing communication for recommending shopping system and optimizing user experience,” Journal of Organizational and End User Computing (JOEUC), vol. 36, no. 1, pp. 1-28, 2024, doi: 10.4018/JOEUC.343258.
B. Rolando and H. Mulyono, “E-commerce as a catalyst for digital economy development: a study of marketing strategies and their impact,” Journal of Distribution Science, vol. 23, no. 4, pp. 61-79, 2025, doi: 10.15722/jds.23.04.202504.61.
R. Hasan, “Enhancing market competitiveness through AI-powered SEO and digital marketing strategies in e-commerce,” ASRC Procedia: Global Perspectives in Science and Scholarship, vol. 1, no. 01, pp. 465-500, 2025, doi: 10.63125/31tpjc54.
M. Yiming, “Research on innovation of cross-border e-commerce marketing channels,” Industrial Engineering and Innovation Management, vol. 6, no. 7, pp. 40-44, 2023, doi: 10.23977/ieim.2023.060706.