Abstract

This paper takes commercial banks' intelligent marketing scenario as the entry point and introduces machine learning into the intelligent marketing scenario. It introduces the range of application and implementation path of machine learning in commercial banks' intelligent marketing solutions, discusses the possible problems and methods in the process of model construction, and gives empirical analysis of simulating scenarios. Emphasis is placed on developing effective marketing strategies and adjusting marketing strategies based on the results of model deployment monitoring to establish a complete intelligent marketing system and closed-loop process. It provides reference for commercial banks to improve marketing response rate and realize digital operation.

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