Exploring the Determinants of Facebook Ad Clicks among Malaysian Users using Machine Learning

This research investigates the factors influencing Facebook users to click on a particular advertisement on the Facebook platform. This research has two main objectives. Firstly, it aims to analyze the relationships between Malaysian Facebook users’ advertisement click behavior with age, gender, day, frequency and engagement. Secondly, this research aims to compare the performance of various machine learning models in predicting Malaysian Facebook users’ advertisement click behaviour. The proposed strategy involves systematic data collection, data preprocessing, data analyzing, data splitting, data training, prediction and comparing performance of various machine learning models. By addressing these objectives, the research hopes to provide valuable insights for businesses to optimize their digital marketing. Engagement with the digital advertisement proves to be main factor in determining whether the user will click on the advertisement. Digital advertisements were also generally clicked towards the end of the week. Moreover, support vector machine proves to be the best model in predicting advertisement clicks among Malaysian Facebook users. In summary, the research was able to investigate the determinants of Facebook Ad clicks among Malaysian users using various machine learning models.

Publication Details

Journal
International Journal of Advanced Research in Computational Thinking and Data Science
Published
2024-12-31
DOI
https://doi.org/10.37934/ctds.4.1.19
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
0.00
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article

Exploring the Determinants of Facebook Ad Clicks among Malaysian Users using Machine Learning

International Journal of Advanced Research in Computational Thinking and Data Science
Digital Marketing and Social Media
article

Exploring the Determinants of Facebook Ad Clicks among Malaysian Users using Machine Learning

article en

Abstract

This research investigates the factors influencing Facebook users to click on a particular advertisement on the Facebook platform. This research has two main objectives. Firstly, it aims to analyze the relationships between Malaysian Facebook users’ advertisement click behavior with age, gender, day, frequency and engagement. Secondly, this research aims to compare the performance of various machine learning models in predicting Malaysian Facebook users’ advertisement click behaviour. The proposed strategy involves systematic data collection, data preprocessing, data analyzing, data splitting, data training, prediction and comparing performance of various machine learning models. By addressing these objectives, the research hopes to provide valuable insights for businesses to optimize their digital marketing. Engagement with the digital advertisement proves to be main factor in determining whether the user will click on the advertisement. Digital advertisements were also generally clicked towards the end of the week. Moreover, support vector machine proves to be the best model in predicting advertisement clicks among Malaysian Facebook users. In summary, the research was able to investigate the determinants of Facebook Ad clicks among Malaysian users using various machine learning models.

International Journal of Advanced Research in Computational Thinking and Data ScienceVol. 4(1)
Gender equality
Openalex Percentile: Top 40%
Digital Marketing and Social Media
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