A Comparative Study of OTT Market Demographic Grouping

Abstract

This research paper aims to analyze the population and potential viewer count for different age groups, genders, and employment status in three distinct clusters of states in the United States. The clusters were formed based on demographic similarities using the K-means clustering for exploration and Hierarchical (Birch and Agglomerative) and Spectral clustering on a dataset that included information on the population, age, gender, employment status, and potential viewers for each state. The research then analyzed the clusters to determine the most significant factors contributing to the viewership in each segment and found that each cluster has unique demographic features, such as a high concentration of younger male viewers in one cluster and older female viewers in another. Additionally, the research identified the states and demographic groups with the highest potential viewership within each cluster. The results section will discuss the demographic features of each cluster, followed by an analysis of the states and demographic groups with the highest potential viewership within each cluster. Our analysis provides valuable insights into the audience's characteristics and preferences, which can be used to optimize marketing and content strategies for the streaming service. The paper will conclude by discussing the implications of these findings and possible future directions for research.