Vol. 5 No. 1 (2025): Issue 5
Articles

Efficient Commercial Advertising Analysis through Probabilistic Logistic Regression

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  • Lotte van Dijk,
  • Jeroen Meijer,
  • Anouk Jansen
Lotte van Dijk
Data Science and Marketing Research Group, Hanze University of Applied Sciences, Groningen, The Netherlands
Jeroen Meijer
Center for Applied Information Technology, Avans University of Applied Sciences, 's-Hertogenbosch, The Netherlands
Anouk Jansen
Institute for Commercial Strategy and Analysis, Saxion University of Applied Sciences, Enschede, The Netherlands

Published 2025-02-26

Keywords

  • Advertising Analysis,
  • Marketing Strategies,
  • Customer Behavior,
  • Probabilistic Modeling,
  • Logistic Regression

How to Cite

Dijk, L. van, Meijer, J., & Jansen, A. (2025). Efficient Commercial Advertising Analysis through Probabilistic Logistic Regression. Journal of Business and Organizational Leadership , 5(1). Retrieved from https://ojs.mri-pub.com/index.php/JBOL/article/view/135

Abstract

Efficient commercial advertising analysis plays a crucial role in optimizing marketing strategies and increasing business revenue. Despite the growing interest in this field, researchers face challenges in accurately predicting advertising effectiveness due to complex customer behavior and diverse advertising channels. In this study, we propose a novel approach utilizing Probabilistic Logistic Regression to model the relationships between advertising campaigns and customer responses. By integrating probabilistic modeling with logistic regression, we aim to enhance the accuracy and efficiency of commercial advertising analysis. Our work not only addresses the current limitations in advertising research but also provides a cutting-edge method for marketers to better understand and target their audience, ultimately leading to improved advertising outcomes and business success.

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