Marketing Automation in E-Commerce: Optimizing Customer Journey, Revenue Generation, and Customer Retention Through Digital Innovation
DOI:
https://doi.org/10.33998/jumanage.2025.4.1.2039Abstrak
This research examines the implementation of marketing automation technologies in optimizing various customer journey touchpoints within e-commerce contexts. Through a comprehensive analysis of peer-reviewed articles from the Scopus database spanning 2020-2024, this study explores how marketing automation, particularly programmatic marketing, leverages advanced data analytics and machine learning to personalize customer interactions and optimize marketing effectiveness. Our systematic review reveals three key findings. First, the strategic implementation of marketing automation significantly enhances revenue generation through improved customer data analytics, predictive modeling, and dynamic pricing strategies, with studies showing increased conversion rates and higher customer lifetime value. Second, marketing automation demonstrates substantial impact on customer retention by enabling personalized experiences and proactive engagement, leading to increased customer satisfaction and loyalty. Third, successful implementation of marketing automation requires robust technological infrastructure, organizational alignment, and continuous optimization of marketing processes. The analysis also highlights that effective integration of predictive analytics and personalization plays a crucial role in driving customer engagement, while the combination of social media analytics and game theory provides businesses with comprehensive frameworks for optimizing competitive strategies. This review contributes to the existing literature by providing a systematic understanding of marketing automation's role in the e-commerce customer journey, highlighting key success factors, implementation challenges, and emerging trends in the field. The findings offer valuable insights for practitioners and researchers interested in leveraging marketing automation for enhanced business performance and competitive advantage in the rapidly evolving e-commerce landscape.
Unduhan
Referensi
Barbosa, B., Saura, J. R., & Bennett, D. (2022). How do entrepreneurs perform digital marketing across the customer journey? A review and discussion of the main uses. The Journal of Technology Transfer. https://doi.org/10.1007/s10961-022-09978-2
Bastos, J. A., & Bernardes, M. I. (2024). Understanding Online Purchases with Explainable Machine Learning. Information, 15(10), 587. https://doi.org/10.3390/info15100587
Baum, J. (2023). Marketing Automation and Customer Loyalty (pp. 213–225). https://doi.org/10.1007/978-3-031-20040-3_13
Bellar, O., Baina, A., & Ballafkih, M. (2024). Sentiment Analysis: Predicting Product Reviews for E-Commerce Recommendations Using Deep Learning and Transformers. Mathematics, 12(15), 2403. https://doi.org/10.3390/math12152403
Chakraborty, A., & Jain, V. (2022). Leveraging Digital Marketing and Integrated Marketing Communications for Brand Building in Emerging Markets (pp. 281–305). https://doi.org/10.1007/978-3-030-88678-3_13
Córdova, F. M., Cifuentes, F., Castro, C., & Hinostroza, C. (2022). Analysis of the purchasing decision-making process in e-commerce using SED Method from Neuromarketing. Procedia Computer Science, 214, 704–711. https://doi.org/10.1016/j.procs.2022.11.232
Dhawas, P., Bondade, A., Patil, S., Khandare, K. S., & Salunkhe, R. V. (2024). Intelligent Automation in Marketing (pp. 66–88). https://doi.org/10.4018/979-8-3693-3354-9.ch003
FRANCESCHETTO, S., CIGOLINI, R., & LAMBERTI, L. (2023). Improving the Supply Chain - Marketing Interface, Translating the Voice of the Customer into Processes. The Eurasia Proceedings of Science Technology Engineering and Mathematics, 23, 471–484. https://doi.org/10.55549/epstem.1371818
Hasan, M. R., Daryanto, Y., Triki, C., & Elomri, A. (2024). An inventory model of e-marketplace with a promotional program. Journal of Modelling in Management, 19(3), 787–808. https://doi.org/10.1108/JM2-01-2023-0011
Holopainen, M., Saunila, M., & Ukko, J. (2023). Facilitating performance measurement and management through digital business strategy. Measuring Business Excellence, 27(2), 246–260. https://doi.org/10.1108/MBE-01-2022-0015
Huang, W.-L., Hu, P., Tsai, S., & Chen, X.-D. (2021). The business analysis on the home-bias of E-commerce consumer behavior. Electronic Commerce Research, 21(3), 855–879. https://doi.org/10.1007/s10660-020-09431-2
Lyu, J. (2021). Will Marketing Automation Encourage Repurchase Intention Through Enhancing Brand Experience? An Empirical Study of Omni-Channel Retailing in China (pp. 401–412). https://doi.org/10.1007/978-981-33-4183-8_32
Mattos, D., Casais, B., & Braga, A. (2021). Marketing Automation in Business-to-Business Relationships and the Emerged Value Cocreation. In COVID-19, Technology and Marketing (pp. 85–99). Springer Nature Singapore. https://doi.org/10.1007/978-981-16-1442-2_5
Mudjahidin, Sholichah, N. L., Aristio, A. P., Junaedi, L., Saputra, Y. A., & Wiratno, S. E. (2022). Purchase intention through search engine marketing: E-marketplace provider in Indonesia. Procedia Computer Science, 197, 445–452. https://doi.org/10.1016/j.procs.2021.12.160
Mulyono, H., & Rolando, B. (2024). Savoring The Success: Cultivating Innovation And Creativity For Indonesian Culinary MSMEs Growth. Economics and Business Journal (ECBIS), 2(4), 413–428.
Okazaki, K., & Inoue, K. (2022). Explainable Model Fusion for Customer Journey Mapping. Frontiers in Artificial Intelligence, 5. https://doi.org/10.3389/frai.2022.824197
Park, J., Hong, E., Ahn, J., & Hyun, H. (2023). Role of multidimensional customer brand engagement on customer behavior for online grocery shopping. Journal of Retailing and Consumer Services, 73, 103380. https://doi.org/10.1016/j.jretconser.2023.103380
R., M., Soju, A. V., & B., S. K. (2024). Artificial Intelligence and Service Marketing Innovation (pp. 150–172). https://doi.org/10.4018/979-8-3693-2153-9.ch007
Raina, A., & Lamkuche, H. (2023). The need for marketing automation: A review. 030013. https://doi.org/10.1063/5.0176843
Rana, J., Jain, R., & Santosh, K. (2023). Automation and AI-Enabled Customer Journey: A Bibliometric Analysis. Vision: The Journal of Business Perspective. https://doi.org/10.1177/09722629221149854
Rolando, B. (2024a). PENGARUH FINTECH TERHADAP INKLUSI KEUANGAN : TINJAUAN SISTEMATIS. Jurnal Akuntansi Dan Bisnis (Akuntansi), 4(2), 50–63. https://doi.org/https://doi.org/10.51903/jiab.v4i2.808
Rolando, B. (2024b). The Role Of Artificial Intelligence In Personalized And Customized Engagement Marketing: A Comprehensive Review. Economics and Business Journal (ECBIS), 2(3), 301–316.
Rolando, B., & Mulyono, H. (2024). UNLOCKING THE POWER OF DATA: EFFECTIVE DATA-DRIVEN MARKETING STRATEGIES TO ENGAGE MILLENNIAL CONSUMERS. TRANSEKONOMIKA: AKUNTANSI, BISNIS DAN KEUANGAN, 4(3), 303–321.
Rolando, B., & Sunara, N. T. (2024). Social Media Marketing’s Effect on Purchase Intentions for Puma: Mediation by Brand Image, Awareness, and Equity. Journal of Business and Economics Research (JBE), 5(3), 340–351.
Rolando, B., & Yen, Y. C. O. (2024). Decoding the TikTok Effect: Influencers, Social Media, and Content Marketing Impact on Consumer Purchases. Journal of Business and Economics Research (JBE), 5(3), 299–310.
Semenda, O., Sokolova, Y., Korovina, O., Bratko, O., & Polishchuk, I. (2024). Using Social Media Analysis to Improve E-commerce Marketing Strategies. International Review of Management and Marketing, 14(4), 61–71. https://doi.org/10.32479/irmm.16196
Singh, B., & Kaunert, C. (2024). Future of Digital Marketing: Hyper-Personalized Customer Dynamic Experience with AI-Based Predictive Models. In Revolutionizing the AI-Digital Landscape (pp. 189–203). Productivity Press. https://doi.org/10.4324/9781032688305-14
Singh, C. P., & Yousuf, R. (2024). Enhancing Marketing Strategies Through Big Data-Driven Customer Journey Mapping: An Analysis Using Machine Learning Algorithms. 2024 International Conference on Emerging Innovations and Advanced Computing (INNOCOMP), 479–484. https://doi.org/10.1109/INNOCOMP63224.2024.00084
Singh, G., Roy, S. K., Apostolidis, C., Quaddus, M., & Sadeque, S. (2025). Identifying the metaverse value recipe(s) affecting customer engagement and well-being in retailing. Technological Forecasting and Social Change, 210, 123870. https://doi.org/10.1016/j.techfore.2024.123870
Singh, J., Nambisan, S., Bridge, R. G., & Brock, J. K.-U. (2021). One-Voice Strategy for Customer Engagement. Journal of Service Research, 24(1), 42–65. https://doi.org/10.1177/1094670520910267
Stone, M., & Woodcock, N. (2021). Developments in B to B and B to C Marketing and Sales Automation Systems. Journal of Business-to-Business Marketing, 28(2), 203–222. https://doi.org/10.1080/1051712X.2021.1920702
Tagashira, T. (2022). Information effects of warehouse automation on sales in omnichannel retailing. Journal of Retailing and Consumer Services, 66, 102903. https://doi.org/10.1016/j.jretconser.2021.102903
Tanuwijaya, M., Mulyono, H., Purnama, B., & Rolando, B. (2024). Pengaruh Kompensasi, Motivasi dan Disiplin Kerja Terhadap Kepuasan Kerja Karyawan. Journal of Trends Economics and Accounting Research, 4(4), 956–967.
Teotia, H., Shishodia, G., Tyagi, E., Prakash, A., & Avasthi, S. (2023). Instagram Analysis and Activity Automation: Using Python and Selenium Automation Tools. 2023 International Conference on Computational Intelligence, Communication Technology and Networking (CICTN), 522–526. https://doi.org/10.1109/CICTN57981.2023.10140356
Trummer, B. (2023). From 0 to 5-Digit-Profit in 10 Weeks with Conversion-Rate-Optimized Marketing and Sales Automation (pp. 97–128). https://doi.org/10.1007/978-3-031-20040-3_8
Waghambare, M., Prabhu, S., Ashok, P., & Natraj, N. A. (2024). Elevating Business Experiences (pp. 1–27). https://doi.org/10.4018/979-8-3693-1503-3.ch001
Wang, T.-C. (2024). Deep Learning-Based Prediction and Revenue Optimization for Online Platform User Journeys. Quantitative Finance and Economics, 8(1), 1–28. https://doi.org/10.3934/QFE.2024001
Wiethölter, J., Salingré, J., Feldmann, C., Schwanitz, J., & Niessing, J. (2023). Exploring Customer Journey Mining and RPA: Prediction of Customers’ Next Touchpoint (pp. 181–196). https://doi.org/10.1007/978-3-031-43433-4_12
Zhang, L., He, J., Yan, Z., Dai, W., & Pani, A. (2020). Application of Genetic Algorithm on Multi-objective Email Marketing Delivery Problem (pp. 309–320). https://doi.org/10.1007/978-981-15-1564-4_29
Zhao, H., Zhao, Z., Xu, A., Gupta, N., & Bay, M. (2023). 2nd Workshop on End-End Customer Journey Optimization. Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 5905–5906. https://doi.org/10.1145/3580305.3599216
