Digital marketing provides a set of tools and strategies to influence purchasing intentions. The research proved that digital ads can positively influence purchasing intentions based on a set of factors. Several studies were conducted to use machine learning in predicting purchasing intentions. The paper demonstrates that digital marketing can generate positive purchasing intentions. However, digital marketing factors that can positively influence purchasing intentions are not widely considered in research that predicts purchasing intentions. This article aims to develop a classification machine learning model to predict the impacts of digital ads on purchasing intentions based on demographics and digital marketing factors. The used dataset was collected from individuals in Saudi Arabia by using     a questionnaire. Two experiments related to feature extraction are applied, and ten different classification machine learning models are evaluated at each experiment. The voting classifier provides an accuracy of 92%, and the random forest provides an accuracy of 91%. They provide good and useful predictions. The results obtained can help marketers to target the right individuals in their digital marketing campaigns.

classification models, digital marketing impact, machine learning, predicting purchasing intentions

Received: October 5, 2024; Accepted: December 10, 2024; Published: December 30, 2024

How to cite this article: Hana Alsaadi, Arwa Wali and Bahjat Fakieh, Predicting impact of digital ads on purchasing intention using machine learning classification models, Advances and Applications in Statistics 92(2) (2025), 303-342. https://doi.org/10.17654/0972361725014

This Open Access Article is Licensed under Creative Commons Attribution 4.0 International License

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