Customer loyalty on the international level is a crucial indicator of a business’s success. Businesses in the interconnected world are competing for customers not only in their own country, but all around the world. Almost all nations have undertaken substantial trade liberalization in the last twenty years and are fast integrating into the global economy. Understanding why some consumers favor global brands while many others choose local, hybrid, or other brands is crucial. Building customer loyalty is a clear objective of any international organization if it wants to keep foreign customers for the long term. Customers will continue to be a loyal client if the product fits and fulfills their needs, as seen by their post-purchase behavior. Consumers in today’s highly competitive market have more sophisticated switching behaviors than ever before because of the widespread availability of information about competing product brands. This research implemented three different classification algorithms, namely, Logistic Regression, K-Nearest Neighbor (KNN), and Support Vector Machine (SVM) to learn the switching behavior of consumers from local brands to international brands. The Support Vector Machine (SVM) performed better among the three algorithms. Glocalization is an intelligent adaptation of thoughts and ideas to local and regional demands, as opposed to having the same products and services everywhere. This study recommends that manufacturers and businesses aim at a worldwide or trans-regional market yet tailored to local laws or culture. Thus, to increase the local interest in global brands, a corporation can follow glocalization and can a global controlling strategy but applies localized methods for target markets depending on their interests, social values, languages, and so on.