Abstract
Unlocking the value of raw data requires transforming it into knowledge and information that drives decision-making. Algorithms for Machine Learning (ML) are capable of analyzing big datasets and delivering accurate predictions. Using machine learning, market segmentation, customer lifetime value, and marketing approaches have been used. This article explores machine learning approaches for marketing, including Support Vector Machines, Genetic Algorithms, Deep Learning, and K-Means. It is rare for ML to be used to forecast when a person will purchase a product or a basket of goods. The survival models Kernel SVM, DeepSurv, Survival Random Forest, and MTLR are evaluated to predict individual tine-purchase choices in this research. Gender, Revenue, Location, Purchase History, Online Behaviour, Interests, and Promotions According to the research, both discounts and CustomerExperience have an impact on the amount of time spent making a purchase. The research indicates that the DeepSurv model best predicted purchase completion. These insights aid in raising conversion rates for marketers.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Data Mining & Knowledge Management Process
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
