Intelligent Customer Acquisition Modeling via Campaign Channel Attribution: A Machine Learning Approach
DOI:
https://doi.org/10.22399/ijcesen.4219Keywords:
Customer Acquisition, Campaign Attribution, Machine Learning, Multi-Channel Marketing, Intelligent ModelingAbstract
The concept of data-driven marketing demands that companies maximize customer acquisition in multi-channel ecosystems. The old attribution models, i.e., last-click or linear models, simplify consumer journeys and fail to provide accurate ROI. Attribution is provided through machine learning, which marks a paradigm shift in approach. It relies on past data and algorithms, combined with contextual information, to improve accuracy. This enables better prediction of acquisition likelihood and more efficient budget allocation. The paper discusses customer acquisition modeling based on machine learning with campaign channel attribution. It explains the underlying principles and explores its real-world applications. The discussion also addresses key constraints and outlines perspectives for future use. In addition, the paper highlights how AI can further enhance effectiveness, personalization, and strategic decision-making in digital markets.
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