Machine Learning-Based Recommender Systems for Digital Marketing
Vikram Singh, Sanjay Tyagi · 2026
Machine learning algorithms have numerous applications in real life. One such machine learning tool —the recommender system—finds application in digital marketing. A recommendation system is a machine learning tool algorithm that may use algorithm(s) belonging to one or more machine learning styles to analyse any user&s;s profile and past behaviour to predict her/his future purchase preferences and make recommendations of products and services based on those predictions. These systems enable business organisations to customise their content, appearance, and other features to individual user&s;s unique interests. This chapter examines various issues involved in using machine learning-based recommendation systems, including their mechanisms, applications, and ethical aspects. The chapter will cover: (1) the discussion on fundamental principles of recommendation systems such as filtering techniques, (2) the potential of machine learning and deep learning techniques to enhance recommendation systems in terms of their accuracy, efficiency, and scalability, and (3) ethical issues related to privacy and data security, and data bias. This chapter aims to offer readers the academic content and resources needed to use machine learning-based recommendation systems in digital marketing strategies effectively.