Using K-Means Clustering to Enhance Digital Marketing with Flight Ticket Search Patterns - Husni Teja Sukmana; Lee Kyung Oh (Bright Publisher, 2024)
This study explores the application of K-Means clustering to enhance digital marketing strategies by analyzing flight ticket search patterns. Utilizing a dataset containing 4,000 search engine results related to flights to Hong Kong, the research identifies five distinct user clusters based on search terms, titles, snippets, and other relevant features. The dataset's key features include search terms, ranks, titles, snippets, display links, and direct links, providing a comprehensive view of user interactions and preferences. The cluster analysis reveals significant variations in user intent and preferences across the identified segments. For instance, Cluster 1 is characterized by users searching for